Robust reception of data utilizing encoded data slices

ABSTRACT

A method begins by a processing module receiving a random order of encoded data slices and interpreting slice names to de-randomize the encoded data slices into of sets of transmit encoded data slices. The method continues with the processing module determining whether a decode threshold number of encoded data slices of a set of transmit encoded data slices have been received. When not received, the method continues with the processing module determining whether a sufficient number of encoded data slices of the set of transmit encoded data slices are still to be received and waiting until the decode threshold number of encoded data slices are received when encoded data slices are still to be received. When the decode threshold number of encoded data slices are received, the method continues with the processing module decoding the decode threshold number of encoded data slices to recapture a corresponding data segment.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. §120 as a continuation of U.S. Utility application Ser. No.13/959,262, entitled “ROBUST RECEPTION OF DATA UTILIZING ENCODED DATASLICES”, filed Aug. 5, 2013, which claims priority pursuant to 35 U.S.C.§119(e) to U.S. Provisional Application No. 61/711,106, entitled“PRIORITIZING TASKS IN A DISTRIBUTED STORAGE AND TASK NETWORK”, filedOct. 8, 2012, both of which are hereby incorporated herein by referencein their entirety and made part of the present U.S. Utility PatentApplication for all purposes.

The present U.S. Utility Patent Application also claims prioritypursuant to 35 U.S.C. §120 as a continuation-in-part of U.S. Utilityapplication Ser. No. 15/230,145, entitled “DISTRIBUTED STORAGE NETWORKAND METHOD FOR STORING AND RETRIEVING ENCRYPTION KEYS”, filed Aug. 5,2016, which is a continuation of U.S. Utility application Ser. No.14/292,727, entitled “DISTRIBUTED STORAGE NETWORK AND METHOD FOR STORINGAND RETRIEVING ENCRYPTION KEYS”, filed May 30, 2014, issued as U.S. Pat.No. 9,413,529 on Aug. 9, 2016, which is a continuation-in-part of U.S.Utility application Ser. No. 13/736,848, entitled “DISTRIBUTED STORAGENETWORK AND METHOD FOR ENCRYPTING AND DECRYPTING DATA USING HASHFUNCTIONS”, filed Jan. 8, 2013, issued as U.S. Pat. No. 9,009,491 onApr. 14, 2015, which is a continuation of U.S. Utility application Ser.No. 12/814,467, entitled “DISTRIBUTED STORAGE NETWORK AND METHOD FORENCRYPTING AND DECRYPTING DATA USING HASH FUNCTIONS”, filed Jun. 13,2010, issued as U.S. Pat. No. 8,351,600 on Jan. 8, 2013, which claimspriority pursuant to 35 U.S.C. §119(e) to U.S. Provisional ApplicationNo. 61/256,411, entitled “DISTRIBUTED STORAGE NETWORK DATA PROCESSING”,filed Oct. 30, 2009, all of which are hereby incorporated herein byreference in their entirety and made part of the present U.S. UtilityPatent Application for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not Applicable

BACKGROUND OF THE INVENTION

Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersed storage of data and distributed taskprocessing of data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system in accordance with the present invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a diagram of an example of a distributed storage and taskprocessing in accordance with the present invention;

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 5 is a logic diagram of an example of a method for outbound DSTprocessing in accordance with the present invention;

FIG. 6 is a schematic block diagram of an embodiment of a dispersederror encoding in accordance with the present invention;

FIG. 7 is a diagram of an example of a segment processing of thedispersed error encoding in accordance with the present invention;

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding in accordance with thepresent invention;

FIG. 9 is a diagram of an example of grouping selection processing ofthe outbound DST processing in accordance with the present invention;

FIG. 10 is a diagram of an example of converting data into slice groupsin accordance with the present invention;

FIG. 11 is a schematic block diagram of an embodiment of a DST executionunit in accordance with the present invention;

FIG. 12 is a schematic block diagram of an example of operation of a DSTexecution unit in accordance with the present invention;

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 14 is a logic diagram of an example of a method for inbound DSTprocessing in accordance with the present invention;

FIG. 15 is a diagram of an example of de-grouping selection processingof the inbound DST processing in accordance with the present invention;

FIG. 16 is a schematic block diagram of an embodiment of a dispersederror decoding in accordance with the present invention;

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of the dispersed error decoding in accordance with thepresent invention;

FIG. 18 is a diagram of an example of a de-segment processing of thedispersed error decoding in accordance with the present invention;

FIG. 19 is a diagram of an example of converting slice groups into datain accordance with the present invention;

FIG. 20 is a diagram of an example of a distributed storage within thedistributed computing system in accordance with the present invention;

FIG. 21 is a schematic block diagram of an example of operation ofoutbound distributed storage and/or task (DST) processing for storingdata in accordance with the present invention;

FIG. 22 is a schematic block diagram of an example of a dispersed errorencoding for the example of FIG. 21 in accordance with the presentinvention;

FIG. 23 is a diagram of an example of converting data into pillar slicegroups for storage in accordance with the present invention;

FIG. 24 is a schematic block diagram of an example of a storageoperation of a DST execution unit in accordance with the presentinvention;

FIG. 25 is a schematic block diagram of an example of operation ofinbound distributed storage and/or task (DST) processing for retrievingdispersed error encoded data in accordance with the present invention;

FIG. 26 is a schematic block diagram of an example of a dispersed errordecoding for the example of FIG. 25 in accordance with the presentinvention;

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing a plurality ofdata and a plurality of task codes in accordance with the presentinvention;

FIG. 28 is a schematic block diagram of an example of the distributedcomputing system performing tasks on stored data in accordance with thepresent invention;

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module facilitating the example of FIG. 28 in accordancewith the present invention;

FIG. 30 is a diagram of a specific example of the distributed computingsystem performing tasks on stored data in accordance with the presentinvention;

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30 in accordance with the presentinvention;

FIG. 32 is a diagram of an example of DST allocation information for theexample of FIG. 30 in accordance with the present invention;

FIGS. 33-38 are schematic block diagrams of the DSTN module performingthe example of FIG. 30 in accordance with the present invention;

FIG. 39 is a diagram of an example of combining result information intofinal results for the example of FIG. 30 in accordance with the presentinvention;

FIG. 40A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 40B is a flowchart illustrating an example of prioritizing arequest in accordance with the present invention;

FIG. 41A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 41B is a flowchart illustrating an example of verifying storageutilization in accordance with the present invention;

FIG. 42A is a diagram of another example of a distributed storage andtask processing in accordance with the present invention;

FIG. 42B is a diagram illustrating an example of allocating data accessrequests and partial tasks to a set of distributed storage and taskexecution (DSTE) units in accordance with the present invention;

FIG. 42C is a diagram illustrating another example of allocating dataaccess requests and partial tasks to a set of distributed storage andtask execution (DSTE) units in accordance with the present invention;

FIG. 42D is a diagram of a pair of tables illustrating an example ofallocating data access requests and partial tasks to a set ofdistributed storage and task execution (DSTE) units in accordance withthe present invention;

FIG. 42E is a diagram of a pair of tables illustrating another exampleof allocating data access requests and partial tasks to a set ofdistributed storage and task execution (DSTE) units in accordance withthe present invention;

FIG. 42F is a diagram illustrating another example of allocating dataaccess requests and partial tasks to a set of distributed storage andtask execution (DSTE) units in accordance with the present invention;

FIG. 42G is a diagram illustrating another example of allocating dataaccess requests and partial tasks to a set of distributed storage andtask execution (DSTE) units in accordance with the present invention;

FIG. 42H is a diagram illustrating another example of allocating dataaccess requests and partial tasks to a set of distributed storage andtask execution (DSTE) units in accordance with the present invention;

FIG. 42I is a diagram of another example of a distributed storage andtask processing in accordance with the present invention;

FIG. 42J is a diagram of another example of a distributed storage andtask processing in accordance with the present invention;

FIG. 42K is a flowchart illustrating an example of load balancing inaccordance with the present invention;

FIG. 43A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 43B is a flowchart illustrating an example of storing data inaccordance with the present invention;

FIG. 44A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 44B is a flowchart illustrating another example of storing data inaccordance with the present invention;

FIG. 45A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 45B is a flowchart illustrating another example of storing data inaccordance with the present invention;

FIG. 45C is a flowchart illustrating another example of retrieving datain accordance with the present invention;

FIG. 45D is a flowchart illustrating another example of rebuilding datain accordance with the present invention;

FIG. 46A is a schematic block diagram of an embodiment of a datacommunication system in accordance with the present invention;

FIG. 46B is a schematic block diagram of another embodiment of a datacommunication system in accordance with the present invention;

FIG. 46C is a schematic block diagram of an embodiment of a data sliceerror coded protocol layer transmit side in accordance with the presentinvention;

FIGS. 46D-G are diagrams illustrating examples of data segment bufferingin accordance with the present invention;

FIG. 46H is a diagram illustrating an example of selecting a subset ofencoded data slices in accordance with the present invention;

FIGS. 46I-J are diagrams illustrating examples of transmit ordering of asubset of encoded data slices in accordance with the present invention;

FIG. 46K is a schematic block diagram of an embodiment of a data sliceerror coded protocol layer receive side in accordance with the presentinvention;

FIGS. 46L-N are diagrams illustrating examples of received ordering ofencoded data slices in accordance with the present invention;

FIG. 46O is a diagram illustrating an example of interrupt transmitordering of encoded data slices in accordance with the presentinvention;

FIG. 46P is a flowchart illustrating an example of encoding data inaccordance with the present invention;

FIG. 46Q is a flowchart illustrating an example of decoding data inaccordance with the present invention;

FIG. 47A is a schematic block diagram of another embodiment of adistributed storage and task (DST) execution unit in accordance with thepresent invention;

FIG. 47B is a flowchart illustrating an example of prioritizing tasks inaccordance with the present invention; and

FIG. 48 is a flowchart illustrating an example of generating a trackingrecord in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system 10 that includes a user device 12 and/or a user device14, a distributed storage and/or task (DST) processing unit 16, adistributed storage and/or task network (DSTN) managing unit 18, a DSTintegrity processing unit 20, and a distributed storage and/or tasknetwork (DSTN) module 22. The components of the distributed computingsystem 10 are coupled via a network 24, which may include one or morewireless and/or wire lined communication systems; one or more privateintranet systems and/or public internet systems; and/or one or morelocal area networks (LAN) and/or wide area networks (WAN).

The DSTN module 22 includes a plurality of distributed storage and/ortask (DST) execution units 36 that may be located at geographicallydifferent sites (e.g., one in Chicago, one in Milwaukee, etc.). Each ofthe DST execution units is operable to store dispersed error encodeddata and/or to execute, in a distributed manner, one or more tasks ondata. The tasks may be a simple function (e.g., a mathematical function,a logic function, an identify function, a find function, a search enginefunction, a replace function, etc.), a complex function (e.g.,compression, human and/or computer language translation, text-to-voiceconversion, voice-to-text conversion, etc.), multiple simple and/orcomplex functions, one or more algorithms, one or more applications,etc.

Each of the user devices 12-14, the DST processing unit 16, the DSTNmanaging unit 18, and the DST integrity processing unit 20 include acomputing core 26 and may be a portable computing device and/or a fixedcomputing device. A portable computing device may be a social networkingdevice, a gaming device, a cell phone, a smart phone, a personal digitalassistant, a digital music player, a digital video player, a laptopcomputer, a handheld computer, a tablet, a video game controller, and/orany other portable device that includes a computing core. A fixedcomputing device may be a personal computer (PC), a computer server, acable set-top box, a satellite receiver, a television set, a printer, afax machine, home entertainment equipment, a video game console, and/orany type of home or office computing equipment. User device 12 and DSTprocessing unit 16 are configured to include a DST client module 34.

With respect to interfaces, each interface 30, 32, and 33 includessoftware and/or hardware to support one or more communication links viathe network 24 indirectly and/or directly. For example, interface 30supports a communication link (e.g., wired, wireless, direct, via a LAN,via the network 24, etc.) between user device 14 and the DST processingunit 16. As another example, interface 32 supports communication links(e.g., a wired connection, a wireless connection, a LAN connection,and/or any other type of connection to/from the network 24) between userdevice 12 and the DSTN module 22 and between the DST processing unit 16and the DSTN module 22. As yet another example, interface 33 supports acommunication link for each of the DSTN managing unit 18 and DSTintegrity processing unit 20 to the network 24.

The distributed computing system 10 is operable to support dispersedstorage (DS) error encoded data storage and retrieval, to supportdistributed task processing on received data, and/or to supportdistributed task processing on stored data. In general and with respectto DS error encoded data storage and retrieval, the distributedcomputing system 10 supports three primary operations: storagemanagement, data storage and retrieval (an example of which will bediscussed with reference to FIGS. 20-26), and data storage integrityverification. In accordance with these three primary functions, data canbe encoded, distributedly stored in physically different locations, andsubsequently retrieved in a reliable and secure manner. Such a system istolerant of a significant number of failures (e.g., up to a failurelevel, which may be greater than or equal to a pillar width minus adecode threshold minus one) that may result from individual storagedevice failures and/or network equipment failures without loss of dataand without the need for a redundant or backup copy. Further, the systemallows the data to be stored for an indefinite period of time withoutdata loss and does so in a secure manner (e.g., the system is veryresistant to attempts at hacking the data).

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has data 40 to store in the DSTN module22, it sends the data 40 to the DST processing unit 16 via its interface30. The interface 30 functions to mimic a conventional operating system(OS) file system interface (e.g., network file system (NFS), flash filesystem (FFS), disk file system (DFS), file transfer protocol (FTP),web-based distributed authoring and versioning (WebDAV), etc.) and/or ablock memory interface (e.g., small computer system interface (SCSI),internet small computer system interface (iSCSI), etc.). In addition,the interface 30 may attach a user identification code (ID) to the data40.

To support storage management, the DSTN managing unit 18 performs DSmanagement services. One such DS management service includes the DSTNmanaging unit 18 establishing distributed data storage parameters (e.g.,vault creation, distributed storage parameters, security parameters,billing information, user profile information, etc.) for a user device12-14 individually or as part of a group of user devices. For example,the DSTN managing unit 18 coordinates creation of a vault (e.g., avirtual memory block) within memory of the DSTN module 22 for a userdevice, a group of devices, or for public access and establishes pervault dispersed storage (DS) error encoding parameters for a vault. TheDSTN managing unit 18 may facilitate storage of DS error encodingparameters for each vault of a plurality of vaults by updating registryinformation for the distributed computing system 10. The facilitatingincludes storing updated registry information in one or more of the DSTNmodule 22, the user device 12, the DST processing unit 16, and the DSTintegrity processing unit 20.

The DS error encoding parameters (e.g., or dispersed storage errorcoding parameters) include data segmenting information (e.g., how manysegments data (e.g., a file, a group of files, a data block, etc.) isdivided into), segment security information (e.g., per segmentencryption, compression, integrity checksum, etc.), error codinginformation (e.g., pillar width, decode threshold, read threshold, writethreshold, etc.), slicing information (e.g., the number of encoded dataslices that will be created for each data segment); and slice securityinformation (e.g., per encoded data slice encryption, compression,integrity checksum, etc.).

The DSTN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSTN module 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSTN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSTN managing unit 18 tracks the number of times a useraccesses a private vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSTNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

Another DS management service includes the DSTN managing unit 18performing network operations, network administration, and/or networkmaintenance. Network operations includes authenticating user dataallocation requests (e.g., read and/or write requests), managingcreation of vaults, establishing authentication credentials for userdevices, adding/deleting components (e.g., user devices, DST executionunits, and/or DST processing units) from the distributed computingsystem 10, and/or establishing authentication credentials for DSTexecution units 36. Network administration includes monitoring devicesand/or units for failures, maintaining vault information, determiningdevice and/or unit activation status, determining device and/or unitloading, and/or determining any other system level operation thataffects the performance level of the system 10. Network maintenanceincludes facilitating replacing, upgrading, repairing, and/or expandinga device and/or unit of the system 10.

To support data storage integrity verification within the distributedcomputing system 10, the DST integrity processing unit 20 performsrebuilding of ‘bad’ or missing encoded data slices. At a high level, theDST integrity processing unit 20 performs rebuilding by periodicallyattempting to retrieve/list encoded data slices, and/or slice names ofthe encoded data slices, from the DSTN module 22. For retrieved encodedslices, they are checked for errors due to data corruption, outdatedversion, etc. If a slice includes an error, it is flagged as a ‘bad’slice. For encoded data slices that were not received and/or not listed,they are flagged as missing slices. Bad and/or missing slices aresubsequently rebuilt using other retrieved encoded data slices that aredeemed to be good slices to produce rebuilt slices. The rebuilt slicesare stored in memory of the DSTN module 22. Note that the DST integrityprocessing unit 20 may be a separate unit as shown, it may be includedin the DSTN module 22, it may be included in the DST processing unit 16,and/or distributed among the DST execution units 36.

To support distributed task processing on received data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task processing) management and DST execution on received data(an example of which will be discussed with reference to FIGS. 3-19).With respect to the storage portion of the DST management, the DSTNmanaging unit 18 functions as previously described. With respect to thetasking processing of the DST management, the DSTN managing unit 18performs distributed task processing (DTP) management services. One suchDTP management service includes the DSTN managing unit 18 establishingDTP parameters (e.g., user-vault affiliation information, billinginformation, user-task information, etc.) for a user device 12-14individually or as part of a group of user devices.

Another DTP management service includes the DSTN managing unit 18performing DTP network operations, network administration (which isessentially the same as described above), and/or network maintenance(which is essentially the same as described above). Network operationsinclude, but are not limited to, authenticating user task processingrequests (e.g., valid request, valid user, etc.), authenticating resultsand/or partial results, establishing DTP authentication credentials foruser devices, adding/deleting components (e.g., user devices, DSTexecution units, and/or DST processing units) from the distributedcomputing system, and/or establishing DTP authentication credentials forDST execution units.

To support distributed task processing on stored data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task) management and DST execution on stored data. With respectto the DST execution on stored data, if the second type of user device14 has a task request 38 for execution by the DSTN module 22, it sendsthe task request 38 to the DST processing unit 16 via its interface 30.An example of DST execution on stored data will be discussed in greaterdetail with reference to FIGS. 27-39. With respect to the DSTmanagement, it is substantially similar to the DST management to supportdistributed task processing on received data.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSTN interface module 76.

The DSTN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). TheDSTN interface module 76 and/or the network interface module 70 mayfunction as the interface 30 of the user device 14 of FIG. 1. Furthernote that the IO device interface module 62 and/or the memory interfacemodules may be collectively or individually referred to as IO ports.

FIG. 3 is a diagram of an example of the distributed computing systemperforming a distributed storage and task processing operation. Thedistributed computing system includes a DST (distributed storage and/ortask) client module 34 (which may be in user device 14 and/or in DSTprocessing unit 16 of FIG. 1), a network 24, a plurality of DSTexecution units 1-n that includes two or more DST execution units 36 ofFIG. 1 (which form at least a portion of DSTN module 22 of FIG. 1), aDST managing module (not shown), and a DST integrity verification module(not shown). The DST client module 34 includes an outbound DSTprocessing section 80 and an inbound DST processing section 82. Each ofthe DST execution units 1-n includes a controller 86, a processingmodule 84, memory 88, a DT (distributed task) execution module 90, and aDST client module 34.

In an example of operation, the DST client module 34 receives data 92and one or more tasks 94 to be performed upon the data 92. The data 92may be of any size and of any content, where, due to the size (e.g.,greater than a few Terabytes), the content (e.g., secure data, etc.),and/or task(s) (e.g., MIPS intensive), distributed processing of thetask(s) on the data is desired. For example, the data 92 may be one ormore digital books, a copy of a company's emails, a large-scale Internetsearch, a video security file, one or more entertainment video files(e.g., television programs, movies, etc.), data files, and/or any otherlarge amount of data (e.g., greater than a few Terabytes).

Within the DST client module 34, the outbound DST processing section 80receives the data 92 and the task(s) 94. The outbound DST processingsection 80 processes the data 92 to produce slice groupings 96. As anexample of such processing, the outbound DST processing section 80partitions the data 92 into a plurality of data partitions. For eachdata partition, the outbound DST processing section 80 dispersed storage(DS) error encodes the data partition to produce encoded data slices andgroups the encoded data slices into a slice grouping 96. In addition,the outbound DST processing section 80 partitions the task 94 intopartial tasks 98, where the number of partial tasks 98 may correspond tothe number of slice groupings 96.

The outbound DST processing section 80 then sends, via the network 24,the slice groupings 96 and the partial tasks 98 to the DST executionunits 1-n of the DSTN module 22 of FIG. 1. For example, the outbound DSTprocessing section 80 sends slice group 1 and partial task 1 to DSTexecution unit 1. As another example, the outbound DST processingsection 80 sends slice group #n and partial task #n to DST executionunit #n.

Each DST execution unit performs its partial task 98 upon its slicegroup 96 to produce partial results 102. For example, DST execution unit#1 performs partial task #1 on slice group #1 to produce a partialresult #1, for results. As a more specific example, slice group #1corresponds to a data partition of a series of digital books and thepartial task #1 corresponds to searching for specific phrases, recordingwhere the phrase is found, and establishing a phrase count. In this morespecific example, the partial result #1 includes information as to wherethe phrase was found and includes the phrase count.

Upon completion of generating their respective partial results 102, theDST execution units send, via the network 24, their partial results 102to the inbound DST processing section 82 of the DST client module 34.The inbound DST processing section 82 processes the received partialresults 102 to produce a result 104. Continuing with the specificexample of the preceding paragraph, the inbound DST processing section82 combines the phrase count from each of the DST execution units 36 toproduce a total phrase count. In addition, the inbound DST processingsection 82 combines the ‘where the phrase was found’ information fromeach of the DST execution units 36 within their respective datapartitions to produce ‘where the phrase was found’ information for theseries of digital books.

In another example of operation, the DST client module 34 requestsretrieval of stored data within the memory of the DST execution units 36(e.g., memory of the DSTN module). In this example, the task 94 isretrieve data stored in the memory of the DSTN module. Accordingly, theoutbound DST processing section 80 converts the task 94 into a pluralityof partial tasks 98 and sends the partial tasks 98 to the respective DSTexecution units 1-n.

In response to the partial task 98 of retrieving stored data, a DSTexecution unit 36 identifies the corresponding encoded data slices 100and retrieves them. For example, DST execution unit #1 receives partialtask #1 and retrieves, in response thereto, retrieved slices #1. The DSTexecution units 36 send their respective retrieved slices 100 to theinbound DST processing section 82 via the network 24.

The inbound DST processing section 82 converts the retrieved slices 100into data 92. For example, the inbound DST processing section 82de-groups the retrieved slices 100 to produce encoded slices per datapartition. The inbound DST processing section 82 then DS error decodesthe encoded slices per data partition to produce data partitions. Theinbound DST processing section 82 de-partitions the data partitions torecapture the data 92.

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module 34 FIG. 1 coupled to a DSTN module 22 of a FIG. 1 (e.g., aplurality of n DST execution units 36) via a network 24. The outboundDST processing section 80 includes a data partitioning module 110, adispersed storage (DS) error encoding module 112, a grouping selectormodule 114, a control module 116, and a distributed task control module118.

In an example of operation, the data partitioning module 110 partitionsdata 92 into a plurality of data partitions 120. The number ofpartitions and the size of the partitions may be selected by the controlmodule 116 via control 160 based on the data 92 (e.g., its size, itscontent, etc.), a corresponding task 94 to be performed (e.g., simple,complex, single step, multiple steps, etc.), DS encoding parameters(e.g., pillar width, decode threshold, write threshold, segment securityparameters, slice security parameters, etc.), capabilities of the DSTexecution units 36 (e.g., processing resources, availability ofprocessing recourses, etc.), and/or as may be inputted by a user, systemadministrator, or other operator (human or automated). For example, thedata partitioning module 110 partitions the data 92 (e.g., 100Terabytes) into 100,000 data segments, each being 1 Gigabyte in size.Alternatively, the data partitioning module 110 partitions the data 92into a plurality of data segments, where some of data segments are of adifferent size, are of the same size, or a combination thereof.

The DS error encoding module 112 receives the data partitions 120 in aserial manner, a parallel manner, and/or a combination thereof. For eachdata partition 120, the DS error encoding module 112 DS error encodesthe data partition 120 in accordance with control information 160 fromthe control module 116 to produce encoded data slices 122. The DS errorencoding includes segmenting the data partition into data segments,segment security processing (e.g., encryption, compression,watermarking, integrity check (e.g., CRC), etc.), error encoding,slicing, and/or per slice security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC), etc.). Thecontrol information 160 indicates which steps of the DS error encodingare active for a given data partition and, for active steps, indicatesthe parameters for the step. For example, the control information 160indicates that the error encoding is active and includes error encodingparameters (e.g., pillar width, decode threshold, write threshold, readthreshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 122 of a datapartition into a set of slice groupings 96. The number of slicegroupings corresponds to the number of DST execution units 36 identifiedfor a particular task 94. For example, if five DST execution units 36are identified for the particular task 94, the grouping selector modulegroups the encoded slices 122 of a data partition into five slicegroupings 96. The grouping selector module 114 outputs the slicegroupings 96 to the corresponding DST execution units 36 via the network24.

The distributed task control module 118 receives the task 94 andconverts the task 94 into a set of partial tasks 98. For example, thedistributed task control module 118 receives a task to find where in thedata (e.g., a series of books) a phrase occurs and a total count of thephrase usage in the data. In this example, the distributed task controlmodule 118 replicates the task 94 for each DST execution unit 36 toproduce the partial tasks 98. In another example, the distributed taskcontrol module 118 receives a task to find where in the data a firstphrase occurs, where in the data a second phrase occurs, and a totalcount for each phrase usage in the data. In this example, thedistributed task control module 118 generates a first set of partialtasks 98 for finding and counting the first phrase and a second set ofpartial tasks for finding and counting the second phrase. Thedistributed task control module 118 sends respective first and/or secondpartial tasks 98 to each DST execution unit 36.

FIG. 5 is a logic diagram of an example of a method for outbounddistributed storage and task (DST) processing that begins at step 126where a DST client module receives data and one or more correspondingtasks. The method continues at step 128 where the DST client moduledetermines a number of DST units to support the task for one or moredata partitions. For example, the DST client module may determine thenumber of DST units to support the task based on the size of the data,the requested task, the content of the data, a predetermined number(e.g., user indicated, system administrator determined, etc.), availableDST units, capability of the DST units, and/or any other factorregarding distributed task processing of the data. The DST client modulemay select the same DST units for each data partition, may selectdifferent DST units for the data partitions, or a combination thereof.

The method continues at step 130 where the DST client module determinesprocessing parameters of the data based on the number of DST unitsselected for distributed task processing. The processing parametersinclude data partitioning information, DS encoding parameters, and/orslice grouping information. The data partitioning information includes anumber of data partitions, size of each data partition, and/ororganization of the data partitions (e.g., number of data blocks in apartition, the size of the data blocks, and arrangement of the datablocks). The DS encoding parameters include segmenting information,segment security information, error encoding information (e.g.,dispersed storage error encoding function parameters including one ormore of pillar width, decode threshold, write threshold, read threshold,generator matrix), slicing information, and/or per slice securityinformation. The slice grouping information includes informationregarding how to arrange the encoded data slices into groups for theselected DST units. As a specific example, if the DST client moduledetermines that five DST units are needed to support the task, then itdetermines that the error encoding parameters include a pillar width offive and a decode threshold of three.

The method continues at step 132 where the DST client module determinestask partitioning information (e.g., how to partition the tasks) basedon the selected DST units and data processing parameters. The dataprocessing parameters include the processing parameters and DST unitcapability information. The DST unit capability information includes thenumber of DT (distributed task) execution units, execution capabilitiesof each DT execution unit (e.g., MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or any other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.)), and/or any information germane toexecuting one or more tasks.

The method continues at step 134 where the DST client module processesthe data in accordance with the processing parameters to produce slicegroupings. The method continues at step 136 where the DST client modulepartitions the task based on the task partitioning information toproduce a set of partial tasks. The method continues at step 138 wherethe DST client module sends the slice groupings and the correspondingpartial tasks to respective DST units.

FIG. 6 is a schematic block diagram of an embodiment of the dispersedstorage (DS) error encoding module 112 of an outbound distributedstorage and task (DST) processing section. The DS error encoding module112 includes a segment processing module 142, a segment securityprocessing module 144, an error encoding module 146, a slicing module148, and a per slice security processing module 150. Each of thesemodules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receives adata partition 120 from a data partitioning module and receivessegmenting information as the control information 160 from the controlmodule 116. The segmenting information indicates how the segmentprocessing module 142 is to segment the data partition 120. For example,the segmenting information indicates how many rows to segment the databased on a decode threshold of an error encoding scheme, indicates howmany columns to segment the data into based on a number and size of datablocks within the data partition 120, and indicates how many columns toinclude in a data segment 152. The segment processing module 142segments the data 120 into data segments 152 in accordance with thesegmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., cyclic redundancy check(CRC), etc.), and/or any other type of digital security. For example,when the segment security processing module 144 is enabled, it maycompress a data segment 152, encrypt the compressed data segment, andgenerate a CRC value for the encrypted data segment to produce a securedata segment 154. When the segment security processing module 144 is notenabled, it passes the data segments 152 to the error encoding module146 or is bypassed such that the data segments 152 are provided to theerror encoding module 146.

The error encoding module 146 encodes the secure data segments 154 inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters (e.g., also referred to as dispersed storage errorcoding parameters) include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an online coding algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction encodingparameters identify a specific error correction encoding scheme,specifies a pillar width of five, and specifies a decode threshold ofthree. From these parameters, the error encoding module 146 encodes adata segment 154 to produce an encoded data segment 156.

The slicing module 148 slices the encoded data segment 156 in accordancewith the pillar width of the error correction encoding parametersreceived as control information 160. For example, if the pillar width isfive, the slicing module 148 slices an encoded data segment 156 into aset of five encoded data slices. As such, for a plurality of encodeddata segments 156 for a given data partition, the slicing module outputsa plurality of sets of encoded data slices 158.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice 158 based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it compresses anencoded data slice 158, encrypts the compressed encoded data slice, andgenerates a CRC value for the encrypted encoded data slice to produce asecure encoded data slice 122. When the per slice security processingmodule 150 is not enabled, it passes the encoded data slices 158 or isbypassed such that the encoded data slices 158 are the output of the DSerror encoding module 112. Note that the control module 116 may beomitted and each module stores its own parameters.

FIG. 7 is a diagram of an example of a segment processing of a dispersedstorage (DS) error encoding module. In this example, a segmentprocessing module 142 receives a data partition 120 that includes 45data blocks (e.g., d1-d45), receives segmenting information (i.e.,control information 160) from a control module, and segments the datapartition 120 in accordance with the control information 160 to producedata segments 152. Each data block may be of the same size as other datablocks or of a different size. In addition, the size of each data blockmay be a few bytes to megabytes of data. As previously mentioned, thesegmenting information indicates how many rows to segment the datapartition into, indicates how many columns to segment the data partitioninto, and indicates how many columns to include in a data segment.

In this example, the decode threshold of the error encoding scheme isthree; as such the number of rows to divide the data partition into isthree. The number of columns for each row is set to 15, which is basedon the number and size of data blocks. The data blocks of the datapartition are arranged in rows and columns in a sequential order (i.e.,the first row includes the first 15 data blocks; the second row includesthe second 15 data blocks; and the third row includes the last 15 datablocks).

With the data blocks arranged into the desired sequential order, theyare divided into data segments based on the segmenting information. Inthis example, the data partition is divided into 8 data segments; thefirst 7 include 2 columns of three rows and the last includes 1 columnof three rows. Note that the first row of the 8 data segments is insequential order of the first 15 data blocks; the second row of the 8data segments in sequential order of the second 15 data blocks; and thethird row of the 8 data segments in sequential order of the last 15 datablocks. Note that the number of data blocks, the grouping of the datablocks into segments, and size of the data blocks may vary toaccommodate the desired distributed task processing function.

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding processing the data segmentsof FIG. 7. In this example, data segment 1 includes 3 rows with each rowbeing treated as one word for encoding. As such, data segment 1 includesthree words for encoding: word 1 including data blocks d1 and d2, word 2including data blocks d16 and d17, and word 3 including data blocks d31and d32. Each of data segments 2-7 includes three words where each wordincludes two data blocks. Data segment 8 includes three words where eachword includes a single data block (e.g., d15, d30, and d45).

In operation, an error encoding module 146 and a slicing module 148convert each data segment into a set of encoded data slices inaccordance with error correction encoding parameters as controlinformation 160. More specifically, when the error correction encodingparameters indicate a unity matrix Reed-Solomon based encodingalgorithm, 5 pillars, and decode threshold of 3, the first three encodeddata slices of the set of encoded data slices for a data segment aresubstantially similar to the corresponding word of the data segment. Forinstance, when the unity matrix Reed-Solomon based encoding algorithm isapplied to data segment 1, the content of the first encoded data slice(DS1_d 1&2) of the first set of encoded data slices (e.g., correspondingto data segment 1) is substantially similar to content of the first word(e.g., d1 & d2); the content of the second encoded data slice (DS1_d16&17) of the first set of encoded data slices is substantially similarto content of the second word (e.g., d16 & d17); and the content of thethird encoded data slice (DS1_d 31&32) of the first set of encoded dataslices is substantially similar to content of the third word (e.g., d31& d32).

The content of the fourth and fifth encoded data slices (e.g., ES1_1 andES1_2) of the first set of encoded data slices include error correctiondata based on the first-third words of the first data segment. With suchan encoding and slicing scheme, retrieving any three of the five encodeddata slices allows the data segment to be accurately reconstructed.

The encoding and slicing of data segments 2-7 yield sets of encoded dataslices similar to the set of encoded data slices of data segment 1. Forinstance, the content of the first encoded data slice (DS2_d 3&4) of thesecond set of encoded data slices (e.g., corresponding to data segment2) is substantially similar to content of the first word (e.g., d3 &d4); the content of the second encoded data slice (DS2_d 18&19) of thesecond set of encoded data slices is substantially similar to content ofthe second word (e.g., d18 & d19); and the content of the third encodeddata slice (DS2_d 33&34) of the second set of encoded data slices issubstantially similar to content of the third word (e.g., d33 & d34).The content of the fourth and fifth encoded data slices (e.g., ES1_1 andES1_2) of the second set of encoded data slices includes errorcorrection data based on the first-third words of the second datasegment.

FIG. 9 is a diagram of an example of grouping selection processing of anoutbound distributed storage and task (DST) processing in accordancewith group selection information as control information 160 from acontrol module. Encoded slices for data partition 122 are grouped inaccordance with the control information 160 to produce slice groupings96. In this example, a grouping selector module 114 organizes theencoded data slices into five slice groupings (e.g., one for each DSTexecution unit of a distributed storage and task network (DSTN) module).As a specific example, the grouping selector module 114 creates a firstslice grouping for a DST execution unit #1, which includes first encodedslices of each of the sets of encoded slices. As such, the first DSTexecution unit receives encoded data slices corresponding to data blocks1-15 (e.g., encoded data slices of contiguous data).

The grouping selector module 114 also creates a second slice groupingfor a DST execution unit #2, which includes second encoded slices ofeach of the sets of encoded slices. As such, the second DST executionunit receives encoded data slices corresponding to data blocks 16-30.The grouping selector module 114 further creates a third slice groupingfor DST execution unit #3, which includes third encoded slices of eachof the sets of encoded slices. As such, the third DST execution unitreceives encoded data slices corresponding to data blocks 31-45.

The grouping selector module 114 creates a fourth slice grouping for DSTexecution unit #4, which includes fourth encoded slices of each of thesets of encoded slices. As such, the fourth DST execution unit receivesencoded data slices corresponding to first error encoding information(e.g., encoded data slices of error coding (EC) data). The groupingselector module 114 further creates a fifth slice grouping for DSTexecution unit #5, which includes fifth encoded slices of each of thesets of encoded slices. As such, the fifth DST execution unit receivesencoded data slices corresponding to second error encoding information.

FIG. 10 is a diagram of an example of converting data 92 into slicegroups that expands on the preceding figures. As shown, the data 92 ispartitioned in accordance with a partitioning function 164 into aplurality of data partitions (1-x, where x is an integer greater than4). Each data partition (or chunkset of data) is encoded and groupedinto slice groupings as previously discussed by an encoding and groupingfunction 166. For a given data partition, the slice groupings are sentto distributed storage and task (DST) execution units. From datapartition to data partition, the ordering of the slice groupings to theDST execution units may vary.

For example, the slice groupings of data partition #1 is sent to the DSTexecution units such that the first DST execution receives first encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a first continuous data chunk of the first data partition(e.g., refer to FIG. 9), a second DST execution receives second encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a second continuous data chunk of the first datapartition, etc.

For the second data partition, the slice groupings may be sent to theDST execution units in a different order than it was done for the firstdata partition. For instance, the first slice grouping of the seconddata partition (e.g., slice group 2_1) is sent to the second DSTexecution unit; the second slice grouping of the second data partition(e.g., slice group 2_2) is sent to the third DST execution unit; thethird slice grouping of the second data partition (e.g., slice group2_3) is sent to the fourth DST execution unit; the fourth slice groupingof the second data partition (e.g., slice group 2_4, which includesfirst error coding information) is sent to the fifth DST execution unit;and the fifth slice grouping of the second data partition (e.g., slicegroup 2_5, which includes second error coding information) is sent tothe first DST execution unit.

The pattern of sending the slice groupings to the set of DST executionunits may vary in a predicted pattern, a random pattern, and/or acombination thereof from data partition to data partition. In addition,from data partition to data partition, the set of DST execution unitsmay change. For example, for the first data partition, DST executionunits 1-5 may be used; for the second data partition, DST executionunits 6-10 may be used; for the third data partition, DST executionunits 3-7 may be used; etc. As is also shown, the task is divided intopartial tasks that are sent to the DST execution units in conjunctionwith the slice groupings of the data partitions.

FIG. 11 is a schematic block diagram of an embodiment of a DST(distributed storage and/or task) execution unit that includes aninterface 169, a controller 86, memory 88, one or more DT (distributedtask) execution modules 90, and a DST client module 34. The memory 88 isof sufficient size to store a significant number of encoded data slices(e.g., thousands of slices to hundreds-of-millions of slices) and mayinclude one or more hard drives and/or one or more solid-state memorydevices (e.g., flash memory, DRAM, etc.).

In an example of storing a slice group, the DST execution modulereceives a slice grouping 96 (e.g., slice group #1) via interface 169.The slice grouping 96 includes, per partition, encoded data slices ofcontiguous data or encoded data slices of error coding (EC) data. Forslice group #1, the DST execution module receives encoded data slices ofcontiguous data for partitions #1 and #x (and potentially others between3 and x) and receives encoded data slices of EC data for partitions #2and #3 (and potentially others between 3 and x). Examples of encodeddata slices of contiguous data and encoded data slices of error coding(EC) data are discussed with reference to FIG. 9. The memory 88 storesthe encoded data slices of slice groupings 96 in accordance with memorycontrol information 174 it receives from the controller 86.

The controller 86 (e.g., a processing module, a CPU, etc.) generates thememory control information 174 based on a partial task(s) 98 anddistributed computing information (e.g., user information (e.g., userID, distributed computing permissions, data access permission, etc.),vault information (e.g., virtual memory assigned to user, user group,temporary storage for task processing, etc.), task validationinformation, etc.). For example, the controller 86 interprets thepartial task(s) 98 in light of the distributed computing information todetermine whether a requestor is authorized to perform the task 98, isauthorized to access the data, and/or is authorized to perform the taskon this particular data. When the requestor is authorized, thecontroller 86 determines, based on the task 98 and/or another input,whether the encoded data slices of the slice grouping 96 are to betemporarily stored or permanently stored. Based on the foregoing, thecontroller 86 generates the memory control information 174 to write theencoded data slices of the slice grouping 96 into the memory 88 and toindicate whether the slice grouping 96 is permanently stored ortemporarily stored.

With the slice grouping 96 stored in the memory 88, the controller 86facilitates execution of the partial task(s) 98. In an example, thecontroller 86 interprets the partial task 98 in light of thecapabilities of the DT execution module(s) 90. The capabilities includeone or more of MIPS capabilities, processing resources (e.g., quantityand capability of microprocessors, CPUs, digital signal processors,co-processor, microcontrollers, arithmetic logic circuitry, and/or anyother analog and/or digital processing circuitry), availability of theprocessing resources, etc. If the controller 86 determines that the DTexecution module(s) 90 have sufficient capabilities, it generates taskcontrol information 176.

The task control information 176 may be a generic instruction (e.g.,perform the task on the stored slice grouping) or a series ofoperational codes. In the former instance, the DT execution module 90includes a co-processor function specifically configured (fixed orprogrammed) to perform the desired task 98. In the latter instance, theDT execution module 90 includes a general processor topology where thecontroller stores an algorithm corresponding to the particular task 98.In this instance, the controller 86 provides the operational codes(e.g., assembly language, source code of a programming language, objectcode, etc.) of the algorithm to the DT execution module 90 forexecution.

Depending on the nature of the task 98, the DT execution module 90 maygenerate intermediate partial results 102 that are stored in the memory88 or in a cache memory (not shown) within the DT execution module 90.In either case, when the DT execution module 90 completes execution ofthe partial task 98, it outputs one or more partial results 102. Thepartial results 102 may also be stored in memory 88.

If, when the controller 86 is interpreting whether capabilities of theDT execution module(s) 90 can support the partial task 98, thecontroller 86 determines that the DT execution module(s) 90 cannotadequately support the task 98 (e.g., does not have the right resources,does not have sufficient available resources, available resources wouldbe too slow, etc.), it then determines whether the partial task 98should be fully offloaded or partially offloaded.

If the controller 86 determines that the partial task 98 should be fullyoffloaded, it generates DST control information 178 and provides it tothe DST client module 34. The DST control information 178 includes thepartial task 98, memory storage information regarding the slice grouping96, and distribution instructions. The distribution instructionsinstruct the DST client module 34 to divide the partial task 98 intosub-partial tasks 172, to divide the slice grouping 96 into sub-slicegroupings 170, and identify other DST execution units. The DST clientmodule 34 functions in a similar manner as the DST client module 34 ofFIGS. 3-10 to produce the sub-partial tasks 172 and the sub-slicegroupings 170 in accordance with the distribution instructions.

The DST client module 34 receives DST feedback 168 (e.g., sub-partialresults), via the interface 169, from the DST execution units to whichthe task was offloaded. The DST client module 34 provides thesub-partial results to the DST execution unit, which processes thesub-partial results to produce the partial result(s) 102.

If the controller 86 determines that the partial task 98 should bepartially offloaded, it determines what portion of the task 98 and/orslice grouping 96 should be processed locally and what should beoffloaded. For the portion that is being locally processed, thecontroller 86 generates task control information 176 as previouslydiscussed. For the portion that is being offloaded, the controller 86generates DST control information 178 as previously discussed.

When the DST client module 34 receives DST feedback 168 (e.g.,sub-partial results) from the DST executions units to which a portion ofthe task was offloaded, it provides the sub-partial results to the DTexecution module 90. The DT execution module 90 processes thesub-partial results with the sub-partial results it created to producethe partial result(s) 102.

The memory 88 may be further utilized to retrieve one or more of storedslices 100, stored results 104, partial results 102 when the DTexecution module 90 stores partial results 102 and/or results 104 in thememory 88. For example, when the partial task 98 includes a retrievalrequest, the controller 86 outputs the memory control 174 to the memory88 to facilitate retrieval of slices 100 and/or results 104.

FIG. 12 is a schematic block diagram of an example of operation of adistributed storage and task (DST) execution unit storing encoded dataslices and executing a task thereon. To store the encoded data slices ofa partition 1 of slice grouping 1, a controller 86 generates writecommands as memory control information 174 such that the encoded slicesare stored in desired locations (e.g., permanent or temporary) withinmemory 88.

Once the encoded slices are stored, the controller 86 provides taskcontrol information 176 to a distributed task (DT) execution module 90.As a first step of executing the task in accordance with the taskcontrol information 176, the DT execution module 90 retrieves theencoded slices from memory 88. The DT execution module 90 thenreconstructs contiguous data blocks of a data partition. As shown forthis example, reconstructed contiguous data blocks of data partition 1include data blocks 1-15 (e.g., d1-d15).

With the contiguous data blocks reconstructed, the DT execution module90 performs the task on the reconstructed contiguous data blocks. Forexample, the task may be to search the reconstructed contiguous datablocks for a particular word or phrase, identify where in thereconstructed contiguous data blocks the particular word or phraseoccurred, and/or count the occurrences of the particular word or phraseon the reconstructed contiguous data blocks. The DST execution unitcontinues in a similar manner for the encoded data slices of otherpartitions in slice grouping 1. Note that with using the unity matrixerror encoding scheme previously discussed, if the encoded data slicesof contiguous data are uncorrupted, the decoding of them is a relativelystraightforward process of extracting the data.

If, however, an encoded data slice of contiguous data is corrupted (ormissing), it can be rebuilt by accessing other DST execution units thatare storing the other encoded data slices of the set of encoded dataslices of the corrupted encoded data slice. In this instance, the DSTexecution unit having the corrupted encoded data slices retrieves atleast three encoded data slices (of contiguous data and of error codingdata) in the set from the other DST execution units (recall for thisexample, the pillar width is 5 and the decode threshold is 3). The DSTexecution unit decodes the retrieved data slices using the DS errorencoding parameters to recapture the corresponding data segment. The DSTexecution unit then re-encodes the data segment using the DS errorencoding parameters to rebuild the corrupted encoded data slice. Oncethe encoded data slice is rebuilt, the DST execution unit functions aspreviously described.

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing section 82 of a DSTclient module coupled to DST execution units of a distributed storageand task network (DSTN) module via a network 24. The inbound DSTprocessing section 82 includes a de-grouping module 180, a DS (dispersedstorage) error decoding module 182, a data de-partitioning module 184, acontrol module 186, and a distributed task control module 188. Note thatthe control module 186 and/or the distributed task control module 188may be separate modules from corresponding ones of outbound DSTprocessing section or may be the same modules.

In an example of operation, the DST execution units have completedexecution of corresponding partial tasks on the corresponding slicegroupings to produce partial results 102. The inbound DST processingsection 82 receives the partial results 102 via the distributed taskcontrol module 188. The inbound DST processing section 82 then processesthe partial results 102 to produce a final result, or results 104. Forexample, if the task was to find a specific word or phrase within data,the partial results 102 indicate where in each of the prescribedportions of the data the corresponding DST execution units found thespecific word or phrase. The distributed task control module 188combines the individual partial results 102 for the correspondingportions of the data into a final result 104 for the data as a whole.

In another example of operation, the inbound DST processing section 82is retrieving stored data from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices 100 corresponding to the data retrieval requests. The de-groupingmodule 180 receives retrieved slices 100 and de-groups them to produceencoded data slices per data partition 122. The DS error decoding module182 decodes, in accordance with DS error encoding parameters, theencoded data slices per data partition 122 to produce data partitions120.

The data de-partitioning module 184 combines the data partitions 120into the data 92. The control module 186 controls the conversion ofretrieved slices 100 into the data 92 using control signals 190 to eachof the modules. For instance, the control module 186 providesde-grouping information to the de-grouping module 180, provides the DSerror encoding parameters to the DS error decoding module 182, andprovides de-partitioning information to the data de-partitioning module184.

FIG. 14 is a logic diagram of an example of a method that is executableby distributed storage and task (DST) client module regarding inboundDST processing. The method begins at step 194 where the DST clientmodule receives partial results. The method continues at step 196 wherethe DST client module retrieves the task corresponding to the partialresults. For example, the partial results include header informationthat identifies the requesting entity, which correlates to the requestedtask.

The method continues at step 198 where the DST client module determinesresult processing information based on the task. For example, if thetask were to identify a particular word or phrase within the data, theresult processing information would indicate to aggregate the partialresults for the corresponding portions of the data to produce the finalresult. As another example, if the task were to count the occurrences ofa particular word or phrase within the data, results of processing theinformation would indicate to add the partial results to produce thefinal results. The method continues at step 200 where the DST clientmodule processes the partial results in accordance with the resultprocessing information to produce the final result or results.

FIG. 15 is a diagram of an example of de-grouping selection processingof an inbound distributed storage and task (DST) processing section of aDST client module. In general, this is an inverse process of thegrouping module of the outbound DST processing section of FIG. 9.Accordingly, for each data partition (e.g., partition #1), thede-grouping module retrieves the corresponding slice grouping from theDST execution units (EU) (e.g., DST 1-5).

As shown, DST execution unit #1 provides a first slice grouping, whichincludes the first encoded slices of each of the sets of encoded slices(e.g., encoded data slices of contiguous data of data blocks 1-15); DSTexecution unit #2 provides a second slice grouping, which includes thesecond encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 16-30); DSTexecution unit #3 provides a third slice grouping, which includes thethird encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 31-45); DSTexecution unit #4 provides a fourth slice grouping, which includes thefourth encoded slices of each of the sets of encoded slices (e.g., firstencoded data slices of error coding (EC) data); and DST execution unit#5 provides a fifth slice grouping, which includes the fifth encodedslices of each of the sets of encoded slices (e.g., first encoded dataslices of error coding (EC) data).

The de-grouping module de-groups the slice groupings (e.g., receivedslices 100) using a de-grouping selector 180 controlled by a controlsignal 190 as shown in the example to produce a plurality of sets ofencoded data slices (e.g., retrieved slices for a partition into sets ofslices 122). Each set corresponding to a data segment of the datapartition.

FIG. 16 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, a de-segmenting processing module 210, and acontrol module 186.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186, unsecures eachencoded data slice 122 based on slice de-security information receivedas control information 190 (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received from thecontrol module 186. The slice security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRCverification, etc.), and/or any other type of digital security. Forexample, when the inverse per slice security processing module 202 isenabled, it verifies integrity information (e.g., a CRC value) of eachencoded data slice 122, it decrypts each verified encoded data slice,and decompresses each decrypted encoded data slice to produce sliceencoded data 158. When the inverse per slice security processing module202 is not enabled, it passes the encoded data slices 122 as the slicedencoded data 158 or is bypassed such that the retrieved encoded dataslices 122 are provided as the sliced encoded data 158.

The de-slicing module 204 de-slices the sliced encoded data 158 intoencoded data segments 156 in accordance with a pillar width of the errorcorrection encoding parameters received as control information 190 fromthe control module 186. For example, if the pillar width is five, thede-slicing module 204 de-slices a set of five encoded data slices intoan encoded data segment 156. The error decoding module 206 decodes theencoded data segments 156 in accordance with error correction decodingparameters received as control information 190 from the control module186 to produce secure data segments 154. The error correction decodingparameters include identifying an error correction encoding scheme(e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction decoding parameters identify a specific errorcorrection encoding scheme, specify a pillar width of five, and specifya decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments 154 based onsegment security information received as control information 190 fromthe control module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module 208 isenabled, it verifies integrity information (e.g., a CRC value) of eachsecure data segment 154, it decrypts each verified secured data segment,and decompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 154 as the data segment152 or is bypassed.

The de-segment processing module 210 receives the data segments 152 andreceives de-segmenting information as control information 190 from thecontrol module 186. The de-segmenting information indicates how thede-segment processing module 210 is to de-segment the data segments 152into a data partition 120. For example, the de-segmenting informationindicates how the rows and columns of data segments are to be rearrangedto yield the data partition 120.

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of a dispersed error decoding module. A de-slicing module 204receives at least a decode threshold number of encoded data slices 158for each data segment in accordance with control information 190 andprovides encoded data 156. In this example, a decode threshold is three.As such, each set of encoded data slices 158 is shown to have threeencoded data slices per data segment. The de-slicing module 204 mayreceive three encoded data slices per data segment because an associateddistributed storage and task (DST) client module requested retrievingonly three encoded data slices per segment or selected three of theretrieved encoded data slices per data segment. As shown, which is basedon the unity matrix encoding previously discussed with reference to FIG.8, an encoded data slice may be a data-based encoded data slice (e.g.,DS1_d 1&d2) or an error code based encoded data slice (e.g., ES3_1).

An error decoding module 206 decodes the encoded data 156 of each datasegment in accordance with the error correction decoding parameters ofcontrol information 190 to produce secured segments 154. In thisexample, data segment 1 includes 3 rows with each row being treated asone word for encoding. As such, data segment 1 includes three words:word 1 including data blocks d1 and d2, word 2 including data blocks d16and d17, and word 3 including data blocks d31 and d32. Each of datasegments 2-7 includes three words where each word includes two datablocks. Data segment 8 includes three words where each word includes asingle data block (e.g., d15, d30, and d45).

FIG. 18 is a diagram of an example of de-segment processing of aninbound distributed storage and task (DST) processing. In this example,a de-segment processing module 210 receives data segments 152 (e.g.,1-8) and rearranges the data blocks of the data segments into rows andcolumns in accordance with de-segmenting information of controlinformation 190 to produce a data partition 120. Note that the number ofrows is based on the decode threshold (e.g., 3 in this specific example)and the number of columns is based on the number and size of the datablocks.

The de-segmenting module 210 converts the rows and columns of datablocks into the data partition 120. Note that each data block may be ofthe same size as other data blocks or of a different size. In addition,the size of each data block may be a few bytes to megabytes of data.

FIG. 19 is a diagram of an example of converting slice groups into data92 within an inbound distributed storage and task (DST) processingsection. As shown, the data 92 is reconstructed from a plurality of datapartitions (1-x, where x is an integer greater than 4). Each datapartition (or chunk set of data) is decoded and re-grouped using ade-grouping and decoding function 212 and a de-partition function 214from slice groupings as previously discussed. For a given datapartition, the slice groupings (e.g., at least a decode threshold perdata segment of encoded data slices) are received from DST executionunits. From data partition to data partition, the ordering of the slicegroupings received from the DST execution units may vary as discussedwith reference to FIG. 10.

FIG. 20 is a diagram of an example of a distributed storage and/orretrieval within the distributed computing system. The distributedcomputing system includes a plurality of distributed storage and/or task(DST) processing client modules 34 (one shown) coupled to a distributedstorage and/or task processing network (DSTN) module, or multiple DSTNmodules, via a network 24. The DST client module 34 includes an outboundDST processing section 80 and an inbound DST processing section 82. TheDSTN module includes a plurality of DST execution units. Each DSTexecution unit includes a controller 86, memory 88, one or moredistributed task (DT) execution modules 90, and a DST client module 34.

In an example of data storage, the DST client module 34 has data 92 thatit desires to store in the DSTN module. The data 92 may be a file (e.g.,video, audio, text, graphics, etc.), a data object, a data block, anupdate to a file, an update to a data block, etc. In this instance, theoutbound DST processing module 80 converts the data 92 into encoded dataslices 216 as will be further described with reference to FIGS. 21-23.The outbound DST processing module 80 sends, via the network 24, to theDST execution units for storage as further described with reference toFIG. 24.

In an example of data retrieval, the DST client module 34 issues aretrieve request to the DST execution units for the desired data 92. Theretrieve request may address each DST executions units storing encodeddata slices of the desired data, address a decode threshold number ofDST execution units, address a read threshold number of DST executionunits, or address some other number of DST execution units. In responseto the request, each addressed DST execution unit retrieves its encodeddata slices 100 of the desired data and sends them to the inbound DSTprocessing section 82, via the network 24.

When, for each data segment, the inbound DST processing section 82receives at least a decode threshold number of encoded data slices 100,it converts the encoded data slices 100 into a data segment. The inboundDST processing section 82 aggregates the data segments to produce theretrieved data 92.

FIG. 21 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module coupled to a distributed storage and task network (DSTN)module (e.g., a plurality of DST execution units) via a network 24. Theoutbound DST processing section 80 includes a data partitioning module110, a dispersed storage (DS) error encoding module 112, a groupingselector module 114, a control module 116, and a distributed taskcontrol module 118.

In an example of operation, the data partitioning module 110 isby-passed such that data 92 is provided directly to the DS errorencoding module 112. The control module 116 coordinates the by-passingof the data partitioning module 110 by outputting a bypass 220 messageto the data partitioning module 110.

The DS error encoding module 112 receives the data 92 in a serialmanner, a parallel manner, and/or a combination thereof. The DS errorencoding module 112 DS error encodes the data in accordance with controlinformation 160 from the control module 116 to produce encoded dataslices 218. The DS error encoding includes segmenting the data 92 intodata segments, segment security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC, etc.)), errorencoding, slicing, and/or per slice security processing (e.g.,encryption, compression, watermarking, integrity check (e.g., CRC,etc.)). The control information 160 indicates which steps of the DSerror encoding are active for the data 92 and, for active steps,indicates the parameters for the step. For example, the controlinformation 160 indicates that the error encoding is active and includeserror encoding parameters (e.g., pillar width, decode threshold, writethreshold, read threshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 218 of thedata segments into pillars of slices 216. The number of pillarscorresponds to the pillar width of the DS error encoding parameters. Inthis example, the distributed task control module 118 facilitates thestorage request.

FIG. 22 is a schematic block diagram of an example of a dispersedstorage (DS) error encoding module 112 for the example of FIG. 21. TheDS error encoding module 112 includes a segment processing module 142, asegment security processing module 144, an error encoding module 146, aslicing module 148, and a per slice security processing module 150. Eachof these modules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receivesdata 92 and receives segmenting information as control information 160from the control module 116. The segmenting information indicates howthe segment processing module is to segment the data. For example, thesegmenting information indicates the size of each data segment. Thesegment processing module 142 segments the data 92 into data segments152 in accordance with the segmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., CRC, etc.), and/or anyother type of digital security. For example, when the segment securityprocessing module 144 is enabled, it compresses a data segment 152,encrypts the compressed data segment, and generates a CRC value for theencrypted data segment to produce a secure data segment. When thesegment security processing module 144 is not enabled, it passes thedata segments 152 to the error encoding module 146 or is bypassed suchthat the data segments 152 are provided to the error encoding module146.

The error encoding module 146 encodes the secure data segments inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction encoding parameters identify a specific errorcorrection encoding scheme, specifies a pillar width of five, andspecifies a decode threshold of three. From these parameters, the errorencoding module 146 encodes a data segment to produce an encoded datasegment.

The slicing module 148 slices the encoded data segment in accordancewith a pillar width of the error correction encoding parameters. Forexample, if the pillar width is five, the slicing module slices anencoded data segment into a set of five encoded data slices. As such,for a plurality of data segments, the slicing module 148 outputs aplurality of sets of encoded data slices as shown within encoding andslicing function 222 as described.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it may compress anencoded data slice, encrypt the compressed encoded data slice, andgenerate a CRC value for the encrypted encoded data slice to produce asecure encoded data slice tweaking. When the per slice securityprocessing module 150 is not enabled, it passes the encoded data slicesor is bypassed such that the encoded data slices 218 are the output ofthe DS error encoding module 112.

FIG. 23 is a diagram of an example of converting data 92 into pillarslice groups utilizing encoding, slicing and pillar grouping function224 for storage in memory of a distributed storage and task network(DSTN) module. As previously discussed the data 92 is encoded and slicedinto a plurality of sets of encoded data slices; one set per datasegment. The grouping selector module organizes the sets of encoded dataslices into pillars of data slices. In this example, the DS errorencoding parameters include a pillar width of 5 and a decode thresholdof 3. As such, for each data segment, 5 encoded data slices are created.

The grouping selector module takes the first encoded data slice of eachof the sets and forms a first pillar, which may be sent to the first DSTexecution unit. Similarly, the grouping selector module creates thesecond pillar from the second slices of the sets; the third pillar fromthe third slices of the sets; the fourth pillar from the fourth slicesof the sets; and the fifth pillar from the fifth slices of the set.

FIG. 24 is a schematic block diagram of an embodiment of a distributedstorage and/or task (DST) execution unit that includes an interface 169,a controller 86, memory 88, one or more distributed task (DT) executionmodules 90, and a DST client module 34. A computing core 26 may beutilized to implement the one or more DT execution modules 90 and theDST client module 34. The memory 88 is of sufficient size to store asignificant number of encoded data slices (e.g., thousands of slices tohundreds-of-millions of slices) and may include one or more hard drivesand/or one or more solid-state memory devices (e.g., flash memory, DRAM,etc.).

In an example of storing a pillar of slices 216, the DST execution unitreceives, via interface 169, a pillar of slices 216 (e.g., pillar #1slices). The memory 88 stores the encoded data slices 216 of the pillarof slices in accordance with memory control information 174 it receivesfrom the controller 86. The controller 86 (e.g., a processing module, aCPU, etc.) generates the memory control information 174 based ondistributed storage information (e.g., user information (e.g., user ID,distributed storage permissions, data access permission, etc.), vaultinformation (e.g., virtual memory assigned to user, user group, etc.),etc.). Similarly, when retrieving slices, the DST execution unitreceives, via interface 169, a slice retrieval request. The memory 88retrieves the slice in accordance with memory control information 174 itreceives from the controller 86. The memory 88 outputs the slice 100,via the interface 169, to a requesting entity.

FIG. 25 is a schematic block diagram of an example of operation of aninbound distributed storage and/or task (DST) processing section 82 forretrieving dispersed error encoded data 92. The inbound DST processingsection 82 includes a de-grouping module 180, a dispersed storage (DS)error decoding module 182, a data de-partitioning module 184, a controlmodule 186, and a distributed task control module 188. Note that thecontrol module 186 and/or the distributed task control module 188 may beseparate modules from corresponding ones of an outbound DST processingsection or may be the same modules.

In an example of operation, the inbound DST processing section 82 isretrieving stored data 92 from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices corresponding to data retrieval requests from the distributedtask control module 188. The de-grouping module 180 receives pillars ofslices 100 and de-groups them in accordance with control information 190from the control module 186 to produce sets of encoded data slices 218.The DS error decoding module 182 decodes, in accordance with the DSerror encoding parameters received as control information 190 from thecontrol module 186, each set of encoded data slices 218 to produce datasegments, which are aggregated into retrieved data 92. The datade-partitioning module 184 is by-passed in this operational mode via abypass signal 226 of control information 190 from the control module186.

FIG. 26 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, and a de-segmenting processing module 210. Thedispersed error decoding module 182 is operable to de-slice and decodeencoded slices per data segment 218 utilizing a de-slicing and decodingfunction 228 to produce a plurality of data segments that arede-segmented utilizing a de-segment function 230 to recover data 92.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186 via controlinformation 190, unsecures each encoded data slice 218 based on slicede-security information (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received as controlinformation 190 from the control module 186. The slice de-securityinformation includes data decompression, decryption, de-watermarking,integrity check (e.g., CRC verification, etc.), and/or any other type ofdigital security. For example, when the inverse per slice securityprocessing module 202 is enabled, it verifies integrity information(e.g., a CRC value) of each encoded data slice 218, it decrypts eachverified encoded data slice, and decompresses each decrypted encodeddata slice to produce slice encoded data. When the inverse per slicesecurity processing module 202 is not enabled, it passes the encodeddata slices 218 as the sliced encoded data or is bypassed such that theretrieved encoded data slices 218 are provided as the sliced encodeddata.

The de-slicing module 204 de-slices the sliced encoded data into encodeddata segments in accordance with a pillar width of the error correctionencoding parameters received as control information 190 from a controlmodule 186. For example, if the pillar width is five, the de-slicingmodule de-slices a set of five encoded data slices into an encoded datasegment. Alternatively, the encoded data segment may include just threeencoded data slices (e.g., when the decode threshold is 3).

The error decoding module 206 decodes the encoded data segments inaccordance with error correction decoding parameters received as controlinformation 190 from the control module 186 to produce secure datasegments. The error correction decoding parameters include identifyingan error correction encoding scheme (e.g., forward error correctionalgorithm, a Reed-Solomon based algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction decodingparameters identify a specific error correction encoding scheme, specifya pillar width of five, and specify a decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments based on segmentsecurity information received as control information 190 from thecontrol module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module is enabled,it verifies integrity information (e.g., a CRC value) of each securedata segment, it decrypts each verified secured data segment, anddecompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 152 as the data segmentor is bypassed. The de-segmenting processing module 210 aggregates thedata segments 152 into the data 92 in accordance with controlinformation 190 from the control module 186.

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module that includes aplurality of distributed storage and task (DST) execution units (#1through #n, where, for example, n is an integer greater than or equal tothree). Each of the DST execution units includes a DST client module 34,a controller 86, one or more DT (distributed task) execution modules 90,and memory 88.

In this example, the DSTN module stores, in the memory of the DSTexecution units, a plurality of DS (dispersed storage) encoded data(e.g., 1 through n, where n is an integer greater than or equal to two)and stores a plurality of DS encoded task codes (e.g., 1 through k,where k is an integer greater than or equal to two). The DS encoded datamay be encoded in accordance with one or more examples described withreference to FIGS. 3-19 (e.g., organized in slice groupings) or encodedin accordance with one or more examples described with reference toFIGS. 20-26 (e.g., organized in pillar groups). The data that is encodedinto the DS encoded data may be of any size and/or of any content. Forexample, the data may be one or more digital books, a copy of acompany's emails, a large-scale Internet search, a video security file,one or more entertainment video files (e.g., television programs,movies, etc.), data files, and/or any other large amount of data (e.g.,greater than a few Terabytes).

The tasks that are encoded into the DS encoded task code may be a simplefunction (e.g., a mathematical function, a logic function, an identifyfunction, a find function, a search engine function, a replace function,etc.), a complex function (e.g., compression, human and/or computerlanguage translation, text-to-voice conversion, voice-to-textconversion, etc.), multiple simple and/or complex functions, one or morealgorithms, one or more applications, etc. The tasks may be encoded intothe DS encoded task code in accordance with one or more examplesdescribed with reference to FIGS. 3-19 (e.g., organized in slicegroupings) or encoded in accordance with one or more examples describedwith reference to FIGS. 20-26 (e.g., organized in pillar groups).

In an example of operation, a DST client module of a user device or of aDST processing unit issues a DST request to the DSTN module. The DSTrequest may include a request to retrieve stored data, or a portionthereof, may include a request to store data that is included with theDST request, may include a request to perform one or more tasks onstored data, may include a request to perform one or more tasks on dataincluded with the DST request, etc. In the cases where the DST requestincludes a request to store data or to retrieve data, the client moduleand/or the DSTN module processes the request as previously discussedwith reference to one or more of FIGS. 3-19 (e.g., slice groupings)and/or 20-26 (e.g., pillar groupings). In the case where the DST requestincludes a request to perform one or more tasks on data included withthe DST request, the DST client module and/or the DSTN module processthe DST request as previously discussed with reference to one or more ofFIGS. 3-19.

In the case where the DST request includes a request to perform one ormore tasks on stored data, the DST client module and/or the DSTN moduleprocesses the DST request as will be described with reference to one ormore of FIGS. 28-39. In general, the DST client module identifies dataand one or more tasks for the DSTN module to execute upon the identifieddata. The DST request may be for a one-time execution of the task or foran on-going execution of the task. As an example of the latter, as acompany generates daily emails, the DST request may be to daily searchnew emails for inappropriate content and, if found, record the content,the email sender(s), the email recipient(s), email routing information,notify human resources of the identified email, etc.

FIG. 28 is a schematic block diagram of an example of a distributedcomputing system performing tasks on stored data. In this example, twodistributed storage and task (DST) client modules 1-2 are shown: thefirst may be associated with a user device and the second may beassociated with a DST processing unit or a high priority user device(e.g., high priority clearance user, system administrator, etc.). EachDST client module includes a list of stored data 234 and a list of taskscodes 236. The list of stored data 234 includes one or more entries ofdata identifying information, where each entry identifies data stored inthe DSTN module 22. The data identifying information (e.g., data ID)includes one or more of a data file name, a data file directory listing,DSTN addressing information of the data, a data object identifier, etc.The list of tasks 236 includes one or more entries of task codeidentifying information, when each entry identifies task codes stored inthe DSTN module 22. The task code identifying information (e.g., taskID) includes one or more of a task file name, a task file directorylisting, DSTN addressing information of the task, another type ofidentifier to identify the task, etc.

As shown, the list of data 234 and the list of tasks 236 are eachsmaller in number of entries for the first DST client module than thecorresponding lists of the second DST client module. This may occurbecause the user device associated with the first DST client module hasfewer privileges in the distributed computing system than the deviceassociated with the second DST client module. Alternatively, this mayoccur because the user device associated with the first DST clientmodule serves fewer users than the device associated with the second DSTclient module and is restricted by the distributed computing systemaccordingly. As yet another alternative, this may occur through norestraints by the distributed computing system, it just occurred becausethe operator of the user device associated with the first DST clientmodule has selected fewer data and/or fewer tasks than the operator ofthe device associated with the second DST client module.

In an example of operation, the first DST client module selects one ormore data entries 238 and one or more tasks 240 from its respectivelists (e.g., selected data ID and selected task ID). The first DSTclient module sends its selections to a task distribution module 232.The task distribution module 232 may be within a stand-alone device ofthe distributed computing system, may be within the user device thatcontains the first DST client module, or may be within the DSTN module22.

Regardless of the task distribution module's location, it generates DSTallocation information 242 from the selected task ID 240 and theselected data ID 238. The DST allocation information 242 includes datapartitioning information, task execution information, and/orintermediate result information. The task distribution module 232 sendsthe DST allocation information 242 to the DSTN module 22. Note that oneor more examples of the DST allocation information will be discussedwith reference to one or more of FIGS. 29-39.

The DSTN module 22 interprets the DST allocation information 242 toidentify the stored DS encoded data (e.g., DS error encoded data 2) andto identify the stored DS error encoded task code (e.g., DS errorencoded task code 1). In addition, the DSTN module 22 interprets the DSTallocation information 242 to determine how the data is to bepartitioned and how the task is to be partitioned. The DSTN module 22also determines whether the selected DS error encoded data 238 needs tobe converted from pillar grouping to slice grouping. If so, the DSTNmodule 22 converts the selected DS error encoded data into slicegroupings and stores the slice grouping DS error encoded data byoverwriting the pillar grouping DS error encoded data or by storing itin a different location in the memory of the DSTN module 22 (i.e., doesnot overwrite the pillar grouping DS encoded data).

The DSTN module 22 partitions the data and the task as indicated in theDST allocation information 242 and sends the portions to selected DSTexecution units of the DSTN module 22. Each of the selected DSTexecution units performs its partial task(s) on its slice groupings toproduce partial results. The DSTN module 22 collects the partial resultsfrom the selected DST execution units and provides them, as resultinformation 244, to the task distribution module. The result information244 may be the collected partial results, one or more final results asproduced by the DSTN module 22 from processing the partial results inaccordance with the DST allocation information 242, or one or moreintermediate results as produced by the DSTN module 22 from processingthe partial results in accordance with the DST allocation information242.

The task distribution module 232 receives the result information 244 andprovides one or more final results 104 therefrom to the first DST clientmodule. The final result(s) 104 may be result information 244 or aresult(s) of the task distribution module's processing of the resultinformation 244.

In concurrence with processing the selected task of the first DST clientmodule, the distributed computing system may process the selectedtask(s) of the second DST client module on the selected data(s) of thesecond DST client module. Alternatively, the distributed computingsystem may process the second DST client module's request subsequent to,or preceding, that of the first DST client module. Regardless of theordering and/or parallel processing of the DST client module requests,the second DST client module provides its selected data 238 and selectedtask 240 to a task distribution module 232. If the task distributionmodule 232 is a separate device of the distributed computing system orwithin the DSTN module, the task distribution modules 232 coupled to thefirst and second DST client modules may be the same module. The taskdistribution module 232 processes the request of the second DST clientmodule in a similar manner as it processed the request of the first DSTclient module.

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module 232 facilitating the example of FIG. 28. The taskdistribution module 232 includes a plurality of tables it uses togenerate distributed storage and task (DST) allocation information 242for selected data and selected tasks received from a DST client module.The tables include data storage information 248, task storageinformation 250, distributed task (DT) execution module information 252,and task

sub-task mapping information 246.

The data storage information table 248 includes a data identification(ID) field 260, a data size field 262, an addressing information field264, distributed storage (DS) information 266, and may further includeother information regarding the data, how it is stored, and/or how itcan be processed. For example, DS encoded data #1 has a data ID of 1, adata size of AA (e.g., a byte size of a few Terabytes or more),addressing information of Addr_1_AA, and DS parameters of 3/5; SEG_1;and SLC_1. In this example, the addressing information may be a virtualaddress corresponding to the virtual address of the first storage word(e.g., one or more bytes) of the data and information on how tocalculate the other addresses, may be a range of virtual addresses forthe storage words of the data, physical addresses of the first storageword or the storage words of the data, may be a list of slice names ofthe encoded data slices of the data, etc. The DS parameters may includeidentity of an error encoding scheme, decode threshold/pillar width(e.g., 3/5 for the first data entry), segment security information(e.g., SEG_1), per slice security information (e.g., SLC_1), and/or anyother information regarding how the data was encoded into data slices.

The task storage information table 250 includes a task identification(ID) field 268, a task size field 270, an addressing information field272, distributed storage (DS) information 274, and may further includeother information regarding the task, how it is stored, and/or how itcan be used to process data. For example, DS encoded task #2 has a taskID of 2, a task size of XY, addressing information of Addr_2_XY, and DSparameters of 3/5; SEG_2; and SLC_2. In this example, the addressinginformation may be a virtual address corresponding to the virtualaddress of the first storage word (e.g., one or more bytes) of the taskand information on how to calculate the other addresses, may be a rangeof virtual addresses for the storage words of the task, physicaladdresses of the first storage word or the storage words of the task,may be a list of slices names of the encoded slices of the task code,etc. The DS parameters may include identity of an error encoding scheme,decode threshold/pillar width (e.g., 3/5 for the first data entry),segment security information (e.g., SEG_2), per slice securityinformation (e.g., SLC_2), and/or any other information regarding howthe task was encoded into encoded task slices. Note that the segmentand/or the per-slice security information include a type of encryption(if enabled), a type of compression (if enabled), watermarkinginformation (if enabled), and/or an integrity check scheme (if enabled).

The task

sub-task mapping information table 246 includes a task field 256 and asub-task field 258. The task field 256 identifies a task stored in thememory of a distributed storage and task network (DSTN) module and thecorresponding sub-task fields 258 indicates whether the task includessub-tasks and, if so, how many and if any of the sub-tasks are ordered.In this example, the task

sub-task mapping information table 246 includes an entry for each taskstored in memory of the DSTN module (e.g., task 1 through task k). Inparticular, this example indicates that task 1 includes 7 sub-tasks;task 2 does not include sub-tasks, and task k includes r number ofsub-tasks (where r is an integer greater than or equal to two).

The DT execution module table 252 includes a DST execution unit ID field276, a DT execution module ID field 278, and a DT execution modulecapabilities field 280. The DST execution unit ID field 276 includes theidentity of DST units in the DSTN module. The DT execution module IDfield 278 includes the identity of each DT execution unit in each DSTunit. For example, DST unit 1 includes three DT executions modules(e.g., 1_1, 1_2, and 1_3). The DT execution capabilities field 280includes identity of the capabilities of the corresponding DT executionunit. For example, DT execution module 1_1 includes capabilities X,where X includes one or more of MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or any other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.), and/or any information germane toexecuting one or more tasks.

From these tables, the task distribution module 232 generates the DSTallocation information 242 to indicate where the data is stored, how topartition the data, where the task is stored, how to partition the task,which DT execution units should perform which partial task on which datapartitions, where and how intermediate results are to be stored, etc. Ifmultiple tasks are being performed on the same data or different data,the task distribution module factors such information into itsgeneration of the DST allocation information.

FIG. 30 is a diagram of a specific example of a distributed computingsystem performing tasks on stored data as a task flow 318. In thisexample, selected data 92 is data 2 and selected tasks are tasks 1, 2,and 3. Task 1 corresponds to analyzing translation of data from onelanguage to another (e.g., human language or computer language); task 2corresponds to finding specific words and/or phrases in the data; andtask 3 corresponds to finding specific translated words and/or phrasesin translated data.

In this example, task 1 includes 7 sub-tasks: task 1_1—identifynon-words (non-ordered); task 1_2—identify unique words (non-ordered);task 1_3—translate (non-ordered); task 1_4—translate back (ordered aftertask 1_3); task 1_5—compare to ID errors (ordered after task 1-4); task1_6—determine non-word translation errors (ordered after task 1_5 and1_1); and task 1_7—determine correct translations (ordered after 1_5 and1_2). The sub-task further indicates whether they are an ordered task(i.e., are dependent on the outcome of another task) or non-order (i.e.,are independent of the outcome of another task). Task 2 does not includesub-tasks and task 3 includes two sub-tasks: task 3_1 translate; andtask 3_2 find specific word or phrase in translated data.

In general, the three tasks collectively are selected to analyze datafor translation accuracies, translation errors, translation anomalies,occurrence of specific words or phrases in the data, and occurrence ofspecific words or phrases on the translated data. Graphically, the data92 is translated 306 into translated data 282; is analyzed for specificwords and/or phrases 300 to produce a list of specific words and/orphrases 286; is analyzed for non-words 302 (e.g., not in a referencedictionary) to produce a list of non-words 290; and is analyzed forunique words 316 included in the data 92 (i.e., how many different wordsare included in the data) to produce a list of unique words 298. Each ofthese tasks is independent of each other and can therefore be processedin parallel if desired.

The translated data 282 is analyzed (e.g., sub-task 3_2) for specifictranslated words and/or phrases 304 to produce a list of specifictranslated words and/or phrases 288. The translated data 282 istranslated back 308 (e.g., sub-task 1_4) into the language of theoriginal data to produce re-translated data 284. These two tasks aredependent on the translate task (e.g., task 1_3) and thus must beordered after the translation task, which may be in a pipelined orderingor a serial ordering. The re-translated data 284 is then compared 310with the original data 92 to find words and/or phrases that did nottranslate (one way and/or the other) properly to produce a list ofincorrectly translated words 294. As such, the comparing task (e.g.,sub-task 1_5) 310 is ordered after the translation 306 andre-translation tasks 308 (e.g., sub-tasks 1_3 and 1_4).

The list of words incorrectly translated 294 is compared 312 to the listof non-words 290 to identify words that were not properly translatedbecause the words are non-words to produce a list of errors due tonon-words 292. In addition, the list of words incorrectly translated 294is compared 314 to the list of unique words 298 to identify unique wordsthat were properly translated to produce a list of correctly translatedwords 296. The comparison may also identify unique words that were notproperly translated to produce a list of unique words that were notproperly translated. Note that each list of words (e.g., specific wordsand/or phrases, non-words, unique words, translated words and/orphrases, etc.)), may include the word and/or phrase, how many times itis used, where in the data it is used, and/or any other informationrequested regarding a word and/or phrase.

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30. As shown, DS encoded data 2 is storedas encoded data slices across the memory (e.g., stored in memories 88)of DST execution units 1-5; the DS encoded task code 1 (of task 1) andDS encoded task 3 are stored as encoded task slices across the memory ofDST execution units 1-5; and DS encoded task code 2 (of task 2) isstored as encoded task slices across the memory of DST execution units3-7. As indicated in the data storage information table and the taskstorage information table of FIG. 29, the respective data/task has DSparameters of 3/5 for their decode threshold/pillar width; hencespanning the memory of five DST execution units.

FIG. 32 is a diagram of an example of distributed storage and task (DST)allocation information 242 for the example of FIG. 30. The DSTallocation information 242 includes data partitioning information 320,task execution information 322, and intermediate result information 324.The data partitioning information 320 includes the data identifier (ID),the number of partitions to split the data into, address information foreach data partition, and whether the DS encoded data has to betransformed from pillar grouping to slice grouping. The task executioninformation 322 includes tabular information having a taskidentification field 326, a task ordering field 328, a data partitionfield ID 330, and a set of DT execution modules 332 to use for thedistributed task processing per data partition. The intermediate resultinformation 324 includes tabular information having a name ID field 334,an ID of the DST execution unit assigned to process the correspondingintermediate result 336, a scratch pad storage field 338, and anintermediate result storage field 340.

Continuing with the example of FIG. 30, where tasks 1-3 are to bedistributedly performed on data 2, the data partitioning informationincludes the ID of data 2. In addition, the task distribution moduledetermines whether the DS encoded data 2 is in the proper format fordistributed computing (e.g., was stored as slice groupings). If not, thetask distribution module indicates that the DS encoded data 2 formatneeds to be changed from the pillar grouping format to the slicegrouping format, which will be done by the DSTN module. In addition, thetask distribution module determines the number of partitions to dividethe data into (e.g., 2_1 through 2_z) and addressing information foreach partition.

The task distribution module generates an entry in the task executioninformation section for each sub-task to be performed. For example, task1_1 (e.g., identify non-words on the data) has no task ordering (i.e.,is independent of the results of other sub-tasks), is to be performed ondata partitions 2_1 through 2_z by DT execution modules 1_1, 2_1, 3_1,4_1, and 5_1. For instance, DT execution modules 1_1, 2_1, 3_1, 4_1, and5_1 search for non-words in data partitions 2_1 through 2_z to producetask 1_1 intermediate results (R1-1, which is a list of non-words). Task1_2 (e.g., identify unique words) has similar task execution informationas task 1_1 to produce task 1_2 intermediate results (R1-2, which is thelist of unique words).

Task 1_3 (e.g., translate) includes task execution information as beingnon-ordered (i.e., is independent), having DT execution modules 1_1,2_1, 3_1, 4_1, and 5_1 translate data partitions 2_1 through 2_4 andhaving DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2 translate datapartitions 2_5 through 2_z to produce task 1_3 intermediate results(R1-3, which is the translated data). In this example, the datapartitions are grouped, where different sets of DT execution modulesperform a distributed sub-task (or task) on each data partition group,which allows for further parallel processing.

Task 1_4 (e.g., translate back) is ordered after task 1_3 and is to beexecuted on task 1_3's intermediate result (e.g., R1-3_1) (e.g., thetranslated data). DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 areallocated to translate back task 1_3 intermediate result partitionsR1-3_1 through R1-3_4 and DT execution modules 1_2, 2_2, 6_1, 7_1, and7_2 are allocated to translate back task 1_3 intermediate resultpartitions R1-3_5 through R1-3_z to produce task 1-4 intermediateresults (R1-4, which is the translated back data).

Task 1_5 (e.g., compare data and translated data to identify translationerrors) is ordered after task 1_4 and is to be executed on task 1_4'sintermediate results (R4-1) and on the data. DT execution modules 1_1,2_1, 3_1, 4_1, and 5_1 are allocated to compare the data partitions (2_1through 2_z) with partitions of task 1-4 intermediate results partitionsR1-4_1 through R1-4_z to produce task 1_5 intermediate results (R1-5,which is the list words translated incorrectly).

Task 1_6 (e.g., determine non-word translation errors) is ordered aftertasks 1_1 and 1_5 and is to be executed on tasks 1_1's and 1_5'sintermediate results (R1-1 and R1-5). DT execution modules 1_1, 2_1,3_1, 4_1, and 5_1 are allocated to compare the partitions of task 1_1intermediate results (R1-1_1 through R1-1_z) with partitions of task 1-5intermediate results partitions (R1-5_1 through R1-5_z) to produce task1_6 intermediate results (R1-6, which is the list translation errors dueto non-words).

Task 1_7 (e.g., determine words correctly translated) is ordered aftertasks 1_2 and 1_5 and is to be executed on tasks 1_2's and 1_5'sintermediate results (R1-1 and R1-5). DT execution modules 1_2, 2_2,3_2, 4_2, and 5_2 are allocated to compare the partitions of task 1_2intermediate results (R1-2_1 through R1-2_z) with partitions of task 1-5intermediate results partitions (R1-5_1 through R1-5_z) to produce task1_7 intermediate results (R1-7, which is the list of correctlytranslated words).

Task 2 (e.g., find specific words and/or phrases) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_1 through 2_z by DT execution modules3_1, 4_1, 5_1, 6_1, and 7_1. For instance, DT execution modules 3_1,4_1, 5_1, 6_1, and 7_1 search for specific words and/or phrases in datapartitions 2_1 through 2_z to produce task 2 intermediate results (R2,which is a list of specific words and/or phrases).

Task 3_2 (e.g., find specific translated words and/or phrases) isordered after task 1_3 (e.g., translate) is to be performed onpartitions R1-3_1 through R1-3_z by DT execution modules 1_2, 2_2, 3_2,4_2, and 5_2. For instance, DT execution modules 1_2, 2_2, 3_2, 4_2, and5_2 search for specific translated words and/or phrases in thepartitions of the translated data (R1-3_1 through R1-3_z) to producetask 3_2 intermediate results (R3-2, which is a list of specifictranslated words and/or phrases).

For each task, the intermediate result information indicates which DSTunit is responsible for overseeing execution of the task and, if needed,processing the partial results generated by the set of allocated DTexecution units. In addition, the intermediate result informationindicates a scratch pad memory for the task and where the correspondingintermediate results are to be stored. For example, for intermediateresult R1-1 (the intermediate result of task 1_1), DST unit 1 isresponsible for overseeing execution of the task 1_1 and coordinatesstorage of the intermediate result as encoded intermediate result slicesstored in memory of DST execution units 1-5. In general, the scratch padis for storing non-DS encoded intermediate results and the intermediateresult storage is for storing DS encoded intermediate results.

FIGS. 33-38 are schematic block diagrams of the distributed storage andtask network (DSTN) module performing the example of FIG. 30. In FIG.33, the DSTN module accesses the data 92 and partitions it into aplurality of partitions 1-z in accordance with distributed storage andtask network (DST) allocation information. For each data partition, theDSTN identifies a set of its DT (distributed task) execution modules 90to perform the task (e.g., identify non-words (i.e., not in a referencedictionary) within the data partition) in accordance with the DSTallocation information. From data partition to data partition, the setof DT execution modules 90 may be the same, different, or a combinationthereof (e.g., some data partitions use the same set while other datapartitions use different sets).

For the first data partition, the first set of DT execution modules(e.g., 1_1, 2_1, 3_1, 4_1, and 5_1 per the DST allocation information ofFIG. 32) executes task 1_1 to produce a first partial result 102 ofnon-words found in the first data partition. The second set of DTexecution modules (e.g., 1_1, 2_1, 3_1, 4_1, and 5_1 per the DSTallocation information of FIG. 32) executes task 1_1 to produce a secondpartial result 102 of non-words found in the second data partition. Thesets of DT execution modules (as per the DST allocation information)perform task 1_1 on the data partitions until the “z” set of DTexecution modules performs task 1_1 on the “zth” data partition toproduce a “zth” partial result 102 of non-words found in the “zth” datapartition.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results toproduce the first intermediate result (R1-1), which is a list ofnon-words found in the data. For instance, each set of DT executionmodules 90 stores its respective partial result in the scratchpad memoryof DST execution unit 1 (which is identified in the DST allocation ormay be determined by DST execution unit 1). A processing module of DSTexecution 1 is engaged to aggregate the first through “zth” partialresults to produce the first intermediate result (e.g., R1_1). Theprocessing module stores the first intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the first intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of non-words is of a sufficient size to partition(e.g., greater than a Terabyte). If yes, it partitions the firstintermediate result (R1-1) into a plurality of partitions (e.g., R1-1_1through R1-1_m). If the first intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the first intermediate result, or for the firstintermediate result, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 34, the DSTN module is performing task 1_2 (e.g., find uniquewords) on the data 92. To begin, the DSTN module accesses the data 92and partitions it into a plurality of partitions 1-z in accordance withthe DST allocation information or it may use the data partitions of task1_1 if the partitioning is the same. For each data partition, the DSTNidentifies a set of its DT execution modules to perform task 1_2 inaccordance with the DST allocation information. From data partition todata partition, the set of DT execution modules may be the same,different, or a combination thereof. For the data partitions, theallocated set of DT execution modules executes task 1_2 to produce apartial results (e.g., 1^(st) through “zth”) of unique words found inthe data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results102 of task 1_2 to produce the second intermediate result (R1-2), whichis a list of unique words found in the data 92. The processing module ofDST execution 1 is engaged to aggregate the first through “zth” partialresults of unique words to produce the second intermediate result. Theprocessing module stores the second intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the second intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of unique words is of a sufficient size to partition(e.g., greater than a Terabyte). If yes, it partitions the secondintermediate result (R1-2) into a plurality of partitions (e.g., R1-2_1through R1-2_m). If the second intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the second intermediate result, or for the secondintermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 35, the DSTN module is performing task 1_3 (e.g., translate) onthe data 92. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions 1-z in accordance with theDST allocation information or it may use the data partitions of task 1_1if the partitioning is the same. For each data partition, the DSTNidentifies a set of its DT execution modules to perform task 1_3 inaccordance with the DST allocation information (e.g., DT executionmodules 1_1, 2_1, 3_1, 4_1, and 5_1 translate data partitions 2_1through 2_4 and DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2translate data partitions 2_5 through 2_z). For the data partitions, theallocated set of DT execution modules 90 executes task 1_3 to producepartial results 102 (e.g., 1^(st) through “zth”) of translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_3 to produce the third intermediate result (R1-3), which istranslated data. The processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of translated data toproduce the third intermediate result. The processing module stores thethird intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the third intermediate result (e.g., translateddata). To begin the encoding, the DST client module partitions the thirdintermediate result (R1-3) into a plurality of partitions (e.g., R1-3_1through R1-3_y). For each partition of the third intermediate result,the DST client module uses the DS error encoding parameters of the data(e.g., DS parameters of data 2, which includes 3/5 decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 2-6 per the DST allocationinformation).

As is further shown in FIG. 35, the DSTN module is performing task 1_4(e.g., retranslate) on the translated data of the third intermediateresult. To begin, the DSTN module accesses the translated data (from thescratchpad memory or from the intermediate result memory and decodes it)and partitions it into a plurality of partitions in accordance with theDST allocation information. For each partition of the third intermediateresult, the DSTN identifies a set of its DT execution modules 90 toperform task 1_4 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 are allocated totranslate back partitions R1-3_1 through R1-3_4 and DT execution modules1_2, 2_2, 6_1, 7_1, and 7_2 are allocated to translate back partitionsR1-3_5 through R1-3_z). For the partitions, the allocated set of DTexecution modules executes task 1_4 to produce partial results 102(e.g., 1^(st) through “zth”) of re-translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_4 to produce the fourth intermediate result (R1-4), which isretranslated data. The processing module of DST execution 3 is engagedto aggregate the first through “zth” partial results of retranslateddata to produce the fourth intermediate result. The processing modulestores the fourth intermediate result as non-DS error encoded data inthe scratchpad memory or in another section of memory of DST executionunit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the fourth intermediate result (e.g., retranslateddata). To begin the encoding, the DST client module partitions thefourth intermediate result (R1-4) into a plurality of partitions (e.g.,R1-4_1 through R1-4_z). For each partition of the fourth intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes 3/5 decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 3-7 per the DST allocationinformation).

In FIG. 36, a distributed storage and task network (DSTN) module isperforming task 1_5 (e.g., compare) on data 92 and retranslated data ofFIG. 35. To begin, the DSTN module accesses the data 92 and partitionsit into a plurality of partitions in accordance with the DST allocationinformation or it may use the data partitions of task 1_1 if thepartitioning is the same. The DSTN module also accesses the retranslateddata from the scratchpad memory, or from the intermediate result memoryand decodes it, and partitions it into a plurality of partitions inaccordance with the DST allocation information. The number of partitionsof the retranslated data corresponds to the number of partitions of thedata.

For each pair of partitions (e.g., data partition 1 and retranslateddata partition 1), the DSTN identifies a set of its DT execution modules90 to perform task 1_5 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1). For each pairof partitions, the allocated set of DT execution modules executes task1_5 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of incorrectly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results oftask 1_5 to produce the fifth intermediate result (R1-5), which is thelist of incorrectly translated words and/or phrases. In particular, theprocessing module of DST execution 1 is engaged to aggregate the firstthrough “zth” partial results of the list of incorrectly translatedwords and/or phrases to produce the fifth intermediate result. Theprocessing module stores the fifth intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the fifth intermediate result. To begin theencoding, the DST client module partitions the fifth intermediate result(R1-5) into a plurality of partitions (e.g., R1-5_1 through R1-5_z). Foreach partition of the fifth intermediate result, the DST client moduleuses the DS error encoding parameters of the data (e.g., DS parametersof data 2, which includes 3/5 decode threshold/pillar width ratio) toproduce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 1-5 per the DST allocation information).

As is further shown in FIG. 36, the DSTN module is performing task 1_6(e.g., translation errors due to non-words) on the list of incorrectlytranslated words and/or phrases (e.g., the fifth intermediate resultR1-5) and the list of non-words (e.g., the first intermediate resultR1-1). To begin, the DSTN module accesses the lists and partitions theminto a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-1_1 and partitionR1-5_1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_6 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1). For each pairof partitions, the allocated set of DT execution modules executes task1_6 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of incorrectly translated words and/or phrases due to non-words.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_6 to produce the sixth intermediate result (R1-6), which is thelist of incorrectly translated words and/or phrases due to non-words. Inparticular, the processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of the list ofincorrectly translated words and/or phrases due to non-words to producethe sixth intermediate result. The processing module stores the sixthintermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the sixth intermediate result. To begin theencoding, the DST client module partitions the sixth intermediate result(R1-6) into a plurality of partitions (e.g., R1-6_1 through R1-6_z). Foreach partition of the sixth intermediate result, the DST client moduleuses the DS error encoding parameters of the data (e.g., DS parametersof data 2, which includes 3/5 decode threshold/pillar width ratio) toproduce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 2-6 per the DST allocation information).

As is still further shown in FIG. 36, the DSTN module is performing task1_7 (e.g., correctly translated words and/or phrases) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of unique words (e.g., the secondintermediate result R1-2). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-2_1 and partitionR1-5_1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_7 in accordance with the DST allocation information(e.g., DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2). For each pairof partitions, the allocated set of DT execution modules executes task1_7 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of correctly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_7 to produce the seventh intermediate result (R1-7), which is thelist of correctly translated words and/or phrases. In particular, theprocessing module of DST execution 3 is engaged to aggregate the firstthrough “zth” partial results of the list of correctly translated wordsand/or phrases to produce the seventh intermediate result. Theprocessing module stores the seventh intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the seventh intermediate result. To begin theencoding, the DST client module partitions the seventh intermediateresult (R1-7) into a plurality of partitions (e.g., R1-7_1 throughR1-7_z). For each partition of the seventh intermediate result, the DSTclient module uses the DS error encoding parameters of the data (e.g.,DS parameters of data 2, which includes 3/5 decode threshold/pillarwidth ratio) to produce slice groupings. The slice groupings are storedin the intermediate result memory (e.g., allocated memory in thememories of DST execution units 3-7 per the DST allocation information).

In FIG. 37, the distributed storage and task network (DSTN) module isperforming task 2 (e.g., find specific words and/or phrases) on the data92. To begin, the DSTN module accesses the data and partitions it into aplurality of partitions 1-z in accordance with the DST allocationinformation or it may use the data partitions of task 1_1 if thepartitioning is the same. For each data partition, the DSTN identifies aset of its DT execution modules 90 to perform task 2 in accordance withthe DST allocation information. From data partition to data partition,the set of DT execution modules may be the same, different, or acombination thereof. For the data partitions, the allocated set of DTexecution modules executes task 2 to produce partial results 102 (e.g.,1^(st) through “zth”) of specific words and/or phrases found in the datapartitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 7 is assigned to process the first through “zth” partial results oftask 2 to produce task 2 intermediate result (R2), which is a list ofspecific words and/or phrases found in the data. The processing moduleof DST execution 7 is engaged to aggregate the first through “zth”partial results of specific words and/or phrases to produce the task 2intermediate result. The processing module stores the task 2intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 7.

DST execution unit 7 engages its DST client module to slice groupingbased DS error encode the task 2 intermediate result. To begin theencoding, the DST client module determines whether the list of specificwords and/or phrases is of a sufficient size to partition (e.g., greaterthan a Terabyte). If yes, it partitions the task 2 intermediate result(R2) into a plurality of partitions (e.g., R2_1 through R2_m). If thetask 2 intermediate result is not of sufficient size to partition, it isnot partitioned.

For each partition of the task 2 intermediate result, or for the task 2intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, and 7).

In FIG. 38, the distributed storage and task network (DSTN) module isperforming task 3 (e.g., find specific translated words and/or phrases)on the translated data (R1-3). To begin, the DSTN module accesses thetranslated data (from the scratchpad memory or from the intermediateresult memory and decodes it) and partitions it into a plurality ofpartitions in accordance with the DST allocation information. For eachpartition, the DSTN identifies a set of its DT execution modules toperform task 3 in accordance with the DST allocation information. Frompartition to partition, the set of DT execution modules may be the same,different, or a combination thereof. For the partitions, the allocatedset of DT execution modules 90 executes task 3 to produce partialresults 102 (e.g., 1^(st) through “zth”) of specific translated wordsand/or phrases found in the data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 5 is assigned to process the first through “zth” partial results oftask 3 to produce task 3 intermediate result (R3), which is a list ofspecific translated words and/or phrases found in the translated data.In particular, the processing module of DST execution 5 is engaged toaggregate the first through “zth” partial results of specific translatedwords and/or phrases to produce the task 3 intermediate result. Theprocessing module stores the task 3 intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 7.

DST execution unit 5 engages its DST client module to slice groupingbased DS error encode the task 3 intermediate result. To begin theencoding, the DST client module determines whether the list of specifictranslated words and/or phrases is of a sufficient size to partition(e.g., greater than a Terabyte). If yes, it partitions the task 3intermediate result (R3) into a plurality of partitions (e.g., R3_1through R3_m). If the task 3 intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the task 3 intermediate result, or for the task 3intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, 5, and 7).

FIG. 39 is a diagram of an example of combining result information intofinal results 104 for the example of FIG. 30. In this example, theresult information includes the list of specific words and/or phrasesfound in the data (task 2 intermediate result), the list of specifictranslated words and/or phrases found in the data (task 3 intermediateresult), the list of non-words found in the data (task 1 firstintermediate result R1-1), the list of unique words found in the data(task 1 second intermediate result R1-2), the list of translation errorsdue to non-words (task 1 sixth intermediate result R1-6), and the listof correctly translated words and/or phrases (task 1 seventhintermediate result R1-7). The task distribution module provides theresult information to the requesting DST client module as the results104.

FIG. 40A is a schematic block diagram of another embodiment of adistributed computing system that includes a plurality of distributedstorage and task (DST) client modules 34 and a DST execution unit 36.The DST client module 34 may be incorporated as part of the DSTprocessing unit 16 or the user device 12 of FIG. 1. The system functionsto prioritize access requests from the plurality of DST client modules34. The access request may include a distributed storage and tasknetwork (DSTN) access request. The DSTN access request may include atleast one of a read request, a write request, a delete request, a listrequest, etc. An access request is executed in accordance with aprioritization scheme and a response 352 is generated based on a resultof executing the request.

The DST client module 34 generates a prioritized request 350 and sendsthe prioritized request 350 to the DST execution unit 36. Theprioritized request 350 may include a task for execution and a desiredpriority level for execution of the task. The DST client module 34selects a value of the desired priority level based on one or more of aprevious response 352 corresponding to the request, a request type ofthe prioritized request 350, the timing requirement, a priority input,and a data type associated with the prioritized request 350.

The DST execution unit 36 determines an execution priority level for theprioritized requests 350 based on one or more of a current loadinglevel, execution priority levels of previously queued requests, and thedesired priority level of the prioritized request 350. The executionpriority level indicates a priority value level relative to otherexecution priority levels of other prioritized requests 350. Forexample, a rejection level indicates that the prioritized request 350will not be executed. As another example, a process level indicates thatthe prioritized request 350 will be executed in accordance with otherqueued prioritized requests 350.

The DST execution unit 36 generates and outputs the response 352 to theDST client module 34, where the response 352 includes the determinedexecution priority level. Next, the DST execution unit 36 executes tasksassociated with the queued prioritized requests 350 in accordance withdetermined execution priority levels. The DST execution unit 36 maygenerate a subsequent response 352 that includes another result ofexecution of tasks associated with another queued prioritized request350. For example, the DST execution unit 36 generates the response 352that includes an encoded data slice when the prioritized request 350includes a request to read the encoded data slice. The method ofoperation of the system to prioritize requests is discussed in greaterdetail with reference to FIG. 40B.

FIG. 40B is a flowchart illustrating an example of prioritizing arequest. The method begins with step 354 where a distributed storage andtask (DST) client module generates a prioritized request. For example,the DST client module generates a read slice request with a higher thanaverage desired priority level value to enable recreation of animportant data file. The method continues at step 356 where the DSTclient module sends the prioritized request to a DST execution unit. Themethod continues at step 358 where the DST execution unit determines anexecution priority level for the prioritized request. The methodcontinues at step 360 where the DST execution unit outputs the executionpriority level to the client module. For example, the DST execution unitgenerates a response that includes the execution priority levelcorresponding to the prioritized request. The method continues at step362 where the DST execution unit executes a task associated with theprioritized request in accordance with the execution priority level andother execution priority levels associated with other tasks of otherprioritized requests.

FIG. 41A is a schematic block diagram of another embodiment of adistributed computing system that includes a distributed storage andtask (DST) client module 34 and a plurality of DST execution units 36.Each DST execution unit 36 of the plurality of DST execution units 36includes a controller 86 and a plurality of memory devices 88. Theplurality of memory devices 88 store encoded data slices 100. The systemfunctions to verify utilization of storage capacity of the plurality ofDST execution units 36 with regards to storage of the encoded dataslices 100.

The DST client module 34 identifies a file for storage analysis. Theidentifying may be based on any of receiving a request, apredetermination, a list, utilizing a round robin approach, andidentifying the file as a next file on a file list. The DST clientmodule 34 generates sets of slice names corresponding to sets of encodeddata slices 100 stored in the DST execution units 36. The file issegmented to produce a plurality of segments. Each segment of theplurality of segments is encoded utilizing a dispersed storage errorcoding function to produce a set of encoded data slices 100. Thegenerating of the sets of slice names may be based on one or more of afile identifier (ID) of the file, a vault ID corresponding to the fileID, and a registry lookup.

The DST client module 34 identifies a set of DST execution units 36associated with storage of the sets of encoded data slices 100. Theidentifying may be based on one or more of receiving identifiers of theset of DST execution units 36, a registry lookup, and a distributedstorage and task network (DSTN) virtual address to physical locationtable lookup.

For each DST execution unit 36 of the set of DST execution units 36, theDST client module 34 generates query requests 364 corresponding to thesets of encoded data slices 100. Each query request 364 includes a slicename corresponding to an encoded data slice 100 of a set of encoded dataslices 100 stored in a memory device 88 of the DST execution unit 36.The DST client module 34 outputs the query request 364 to the DSTexecution unit 36.

A corresponding controller 86 of the DST execution unit 36 receives thequery request 364 and identifies the memory device 88 that is utilizedto store the encoded data slice 100. The DST execution unit 36 generatesa query response 366. The query response 366 includes one or more of theslice name, storage location information which includes an identifier ofthe memory device 88, a length of time of storage indicator, a memorydevice age, and a memory device replacement schedule. The generatingincludes at least one of accessing a local table and retrievinginformation from the memory device 88. The DST execution unit 36 outputsthe query response 366 to the DST client module 34

For the set of encoded data slices 100, the DST client module 34receives a set of query responses 366 from the set of DST executionunits 36. The DST client module 34 facilitates a storage action based onthe set of query responses 366. A first storage action includesgenerating a storage record that includes one or more of the file ID, asource name corresponding to the file ID, identity of the data segments,the sets of slice names, identity of the set of DST execution units 36,and the storage location information within the set of DST executionunits 36. A second storage action includes migrating at least someencoded data slices 100 when the storage record compares unfavorably toa desired storage record. For example, the DST client module 34 detectsan imbalance based on the comparison and indicates to migrate the atleast some encoded data slices 100. The method to verify storageutilization is discussed in greater detail with reference to FIG. 41B.

FIG. 41B is a flowchart illustrating an example of verifying storageutilization. The method begins with step 368 where a processing module(e.g., of a distributed storage and task (DST) client module) obtains adata identifier (ID) for slice location identification. The obtainingincludes at least one of receiving, initiating a query, extracting froman error message, and receiving a user request. The method continues atstep 370 where the processing module identifies a source name (e.g., avirtual distributed storage and task network (DSTN) address)corresponding to the data ID as a specific example, the processingmodule performs a directory lookup utilizing the data ID to extract thesource name from a DSTN directory. The method continues at step 372where the processing module identifies a plurality of data segments. Theidentifying includes at least one of extracting identities from asegment allocation table associated with the source name and extractingfrom a first retrieved data segment associated with the source name.

For each data segment, the method continues at step 374 where theprocessing module generates a set of slice names. Each slice nameincludes the source name and a segment number in accordance with aplurality of data segments. The method continues at step 376 where theprocessing module identifies a set of DST execution units based on setsof slice names. The identifying includes accessing a slice name tophysical location table utilizing the set of slice names.

For each data segment, the method continues at step 378 where theprocessing module generates a set of query requests that includes acorresponding set of slice names. For each data segment, the methodcontinues at step 380 where the processing module sends the set of queryrequests to the set of DST execution units. The method continues at step382 where the processing module receives sets of query requests. Themethod continues at step 384 where the processing module generates astorage record that includes the data identifier, the source name,identity of the data segments, the sets of slice names, identity of theset of DST execution units, and storage location information of the setsof query responses. Alternatively, or in addition to, the processingmodule may graphically display information of the storage record.

The method continues at step 386 where the processing module facilitatesmigration of at least some encoded data slices associated with the setsof slice names when the storage record compares unfavorably to a desiredstorage record. The facilitating includes identifying the encoded dataslices based on the comparison. For example, a processing moduleidentifies the encoded data slices to migrate when a memory deviceidentifier of the storage location information is associated with anunfavorable reliability level.

FIG. 42A is a diagram of another example of a distributed storage andtask (DST) processing that includes the DST client module 34, thenetwork 24, and the set of DST execution (DSTE) units of FIG. 3. The DSTclient module 34 includes the outbound DST processing module 80 and theinbound DST processing module 82 of FIG. 3, and an efficiency module388. The set of DSTE units, from unit to unit, may have differentstorage and task processing capabilities and availability. Accordingly,it may be desired to allocate an imbalance of utilization of the taskprocessing and storage capabilities to achieve a desired utilization ofthe set of DSTE units (e.g., utilizing substantially most of allcapabilities of each unit). The DST client module 34 processes aplurality of data access requests 390 and a request to execute adistributed computing function 391 in a manner to achieve the desiredutilization of the set of DSTE units. The data access requests 390request access to a plurality of data files 1-x, where each data fileincludes a plurality of sets of encoded data slices 1-n stored in theset of DSTE units.

In an example of achieving the desired utilization of the set of DSTEunits, the outbound DST processing module 80 obtains (e.g., receives,creates) the plurality of data access requests 390 and the request toexecute the distributed computing function 391 that includes a pluralityof partial tasks 98. As a specific example, the outbound DST processingmodule 80 receives the request execute the distributed computingfunction 391 and generates the plurality of partial tasks 98. As anotherspecific example, the outbound DST processing module 80 receives theplurality of partial tasks 98. The outbound DST processing module 80 mayobtain the plurality of data access requests 390 and the request toexecute the distributed computing function 391 overlapping in time. Forexample, the outbound DST processing 80 receives the plurality of dataaccess requests 390 regarding storage of a data file and obtains therequest to execute the distributed computing function 391 regarding thedata file. During the overlapping time, the efficiency module 388 mayestablish the desired utilization of the set of DSTE units tosubstantially balance loading of the DSTE units based on per unitprocessing resource utilization to processing resource capabilities. Theefficiency module 388 outputs efficiency information 394 to the outboundDST processing module 80, where the efficiency information 394 includesthe desired utilization of the set of DSTE units. For example, theoutbound DST processing 80 establishes the desired utilization toinclude a higher resource utilization for one DSTE unit when that DSTEunit has higher processing resource capabilities than other DSTE units.

Having received the established desired utilization of the set of DSTEunits, the outbound DST processing module 80 establishes a desiredexecuting efficiency and a desired data access efficiency to obtain thedesired utilization of the set of DSTE units. As a specific example ofestablishing the desired data access efficiency, when the plurality ofdata access requests 390 includes a plurality of write requestsregarding storing the data file as the plurality of sets of encoded dataslices in the set of DSTE units, the outbound DST processing module 80determines a write threshold that indicates, for a set of encoded dataslices, a number of encoded data slices to write to the set of DSTEunits to ensure proper storage of a data segment of the data file.Having established the write threshold, the outbound DST processingmodule 80 establishes the desired data access efficiency based on thewrite threshold.

As another specific example of establishing the desired data accessefficiency, when the plurality of data access requests 390 including aplurality of read requests regarding reading a data file from the set ofDSTE units as a plurality of sets of encoded data slices, the outboundDST processing module 80 determines a read threshold that indicates, forthe set of encoded data slices, a number of encoded data slices to readto ensure recovery of a data segment of the data file from the number ofencoded data slices. Having established the read threshold, the outboundDST processing module 80 establishes the desired data access efficiencybased on the read threshold.

Having established the desired data access efficiency and the desiredexecuting efficiency, the outbound DST processing module 80 allocatesexecution of the plurality of partial tasks 98 to the set of DSTE unitsin accordance with the desired executing efficiency. The outbound DSTprocessing module 80 distributes execution of the plurality of partialtasks 98 among the set of DSTE units such that, from time-to-time,differing DSTE units of the set of DSTE units are not assigned executionof a partial task of the plurality of partial tasks. For example, theoutbound DST processing module 80 distributes execution of the pluralityof partial tasks 98 such that each DSTE unit is assigned one partialtask 98 of a set of five partial tasks 98 when the set of DSTE unitsincludes five DSTE units. The DST processing module 80 may distributethe execution equally amongst the DSTE units or in an imbalanced manner.As a specific example of equal distribution, the outbound DST processingmodule 80 distributes execution substantially equally allocating theplurality of partial tasks 98 among the set of DSTE units utilizing apattern to provide the substantially equally allocation. For instance,the pattern indicates on a DSTE unit by DSTE unit basis of when and whennot a DSTE unit of the set of DSTE units is allocated a partial task 98.As a specific example of imbalanced distribution, the outbound DSTprocessing module 80 allocates in an imbalanced manner, the plurality ofpartial tasks 98 among the set of DSTE units. For instance, the outboundDST processing module allocates 4 partial tasks 98 to a first DSTE unitand allocates no partial tasks to a second DSTE unit.

Having allocated execution of the plurality of partial tasks 98, theoutbound DST processing module 80 allocates processing of the pluralityof data access requests 390 to the set of DSTE units in accordance withthe desired data access efficiency. The outbound DST processing module80 sends allocated access requests 392 of the plurality of data accessrequests 390 among the set of DSTE units such that, from time-to-time,differing DSTE units are not processing an allocated data access request392 of the plurality of data access requests 390.

The DST processing module 80 may allocate the allocated data accessrequests 392 equally amongst the DSTE units or in an imbalanced manner.As a specific example of equal allocation, the outbound DST processingmodule 80 substantially equally allocates the plurality of data accessrequests 390 to the set of DSTE units utilizing a pattern (e.g., adifferent unit is skipped in a round-robin fashion for each set ofaccess slice requests) to provide the substantially equally allocation.For instance, the pattern indicates on a DSTE unit by DSTE unit basis ofwhen and when not a DSTE unit of the set of DSTE units is allocated anallocated data access request 392. As a specific example of imbalancedallocation, the outbound DST processing module 80 allocates, in theimbalanced manner, the plurality of data access requests to the set ofDSTE units. For instance, a series of 10 sets of access slice requestsincludes a first 4 DSTE units and excludes a 5th DSTE unit.

FIG. 42B is a diagram illustrating an example of allocating data accessrequests and partial tasks to a set of distributed storage and taskexecution (DSTE) units in accordance with desired utilization of the setof DSTE units to achieve balanced utilization. The data access requestsincludes at least one of reading, writing, deleting, and listing. Theallocating includes allocating one or both of a data access request anda partial task to a common time interval of a series of time intervals.The data access request includes accessing at least one of an encodeddata slice for a data segment and a group of encoded data slices for acorresponding group of data segments. For example, a data access requestfor a first encoded data slice of a first data segment may be allocatedto a first time interval and another data access request for a secondencoded data slice of a second data segment may be allocated to a secondtime interval. As another example, a data access request for a group offirst encoded data slices of a corresponding group of data segments maybe allocated to the first time interval and another data access requestfor another group of second encoded data slices of the correspondinggroup of data segments may be allocated to the second time interval.

The allocating of the data access requests and partial tasks illustratesan example of a utilization of a balanced approach for both data accessrequests and partial tasks. In this example, a repeating pattern of fivetime intervals is chosen where the number of time intervals for therepeating pattern can be any number and perhaps as a function of thedesired utilization of the set of DSTE units. In this example, over timeintervals 1-5, each DSTE unit is assigned four data access requests offive data access requests 1-5 for a corresponding four time intervalsand an fifth time interval with no data access request assignment. Overthe time intervals 1-5, each DSTE unit is assigned one partial task ofpartial tasks 1-5 for one time interval and no partial tasks for aremaining four other time intervals.

FIG. 42C is a diagram illustrating another example of allocating dataaccess requests and partial tasks to a set of distributed storage andtask execution (DSTE) units continuing the example of FIG. 42B inaccordance with desired utilization of the set of DSTE units to achievethe balanced utilization. The allocating of the data access requests andpartial tasks continues the example of utilization of the balancedapproach for both data access requests and partial tasks. When changingfrom a time interval group (e.g., from the previous five time intervals)to a new time interval group (e.g., this example), the repeating patternmay change (e.g., number of allocated data access requests, number ofallocated partial tasks) and/or the number of time intervals per groupmay be changed (e.g., moving from five time intervals per time intervalgroup to eight time intervals per time interval group).

In the continued example, the repeating pattern of five time intervalsis continued to be used. In the continued example, over time intervals6-10, each DSTE unit is assigned four data access requests of five dataaccess requests 6-10 for a corresponding four time intervals and a fifthtime interval with no data access request assignment matching a previouspattern of five time intervals of FIG. 42B. Over the time intervals6-20, each DSTE unit is assigned one partial task of partial tasks 6-10for one time interval and no partial tasks for a remaining four othertime intervals matching the previous pattern of five time intervals ofFIG. 42B.

FIG. 42D is a diagram of a pair of tables illustrating an example ofallocating data access requests and partial tasks to a set ofdistributed storage and task execution (DSTE) units with desired DSTEunit utilization to achieve the balanced utilization. The illustratingof the allocating includes a data access processing table 396 and apartial task processing table 398. The tables correspond to the examplesof allocation of data access requests and partial tasks to the set ofDSTE units discussed with reference to FIGS. 42B-C. For example, thedata access processing table 396 illustrates assignment of data accessrequests associated with time intervals 1-4 of a first time intervalgroup and another data access request associated with time interval 6 ofa second time interval group to a first DSTE unit. As another example,the partial task processing table 398 illustrates assignment of apartial task associated with time interval 1 for the first time intervalgroup and another partial task associated with time interval 6 of thesecond time interval group to a fifth DSTE unit.

FIG. 42E is a diagram of a pair of tables illustrating another exampleof allocating data access requests and partial tasks to a set ofdistributed storage and task execution (DSTE) units with desired DSTEunit utilization to achieve the balanced utilization. The illustratingof the allocating includes a data access processing table 400 and apartial task processing table 402. The example illustrates a first timeinterval group that includes 15 time intervals and a pattern that isidentical for every three time intervals. Each DSTE unit is assigneddata access requests associated with four sets of three identical timeintervals for a total of 12 time intervals out of the 15 time intervalsof the first time interval group. For instance, the data accessprocessing table 400 illustrates that a first DSTE unit is assigned dataaccess requests associated with time intervals 1-12 and not with timeintervals 13-15. As another instance, the partial task processing table402 illustrates that the first DSTE unit is assigned partial tasksassociated with time intervals 13-15 and no partial tasks for timeintervals 1-12. The cycle may repeat in a second time interval group.

FIGS. 42F-H are diagrams illustrating other examples of allocating dataaccess requests and partial tasks to a set of distributed storage andtask execution (DSTE) units to achieve a desired DSTE unit utilizationwhen DSTE resource capabilities are imbalanced. The allocation includesallocating the data access requests and the partial tasks in accordancewith the imbalance of resource capabilities. The imbalance of resourcecapabilities includes at least one of an imbalance of storagecapabilities and an imbalance of task processing capabilities. Theallocating includes balancing data access requests when storagecapabilities are balanced and allocating imbalanced data access requestswhen the storage capabilities are imbalanced. The allocating furtherincludes balancing partial task requests when partial task processingcapabilities are balanced and allocating imbalanced partial taskrequests when the partial task processing capabilities are imbalanced.FIG. 42F illustrates an example where the data access requests areallocated in a balanced manner and the partial task requests areallocated in the imbalanced manner. FIG. 42G illustrates another examplewhere allocation of the data access requests are allocated in theimbalanced manner and the partial tasks are allocated in the balancedmanner. FIG. 42H illustrates yet another example where both theallocation of the data access requests and the partial tasks areallocated in the imbalanced manner.

In particular, FIG. 42F illustrates an example when a fifth DSTE unithas more task executing resource capability than other DSTE units buteach DSTE unit has similar data access resource capability. Accordingly,the fifth DSTE unit is allocated partial tasks 1-3 in addition to dataaccess requests 1, 3, 4, and 5 while a third and a fourth DSTE unit withminimal task executing resource capability are not allocated any partialtasks. Each DSTE unit is allocated 4 data access requests within thefive time interval time interval group.

FIG. 42G illustrates an example when the first, the second, and thefifth DSTE units have more data access resource capability than otherDSTE units but each DSTE unit has similar task executing resourcecapability. Accordingly, the first and the fifth DSTE units areallocated five data access requests, the second DSTE unit is allocatedfour data access requests, and the third and fourth DSTE units are onlyallocated three data access requests. Each DSTE unit is allocated onepartial task within the five time interval time interval group.

FIG. 42H illustrates an example when the first and the fifth DSTE unitshave more data access resource capabilities than other DSTE units. Forexample, the first and the fifth DSTE units are newer models withexpanded memory and expanded task processing power. Accordingly, thefirst and the fifth DSTE units are allocated five data access requestsand two partial tasks during the five time interval time interval group.The second DSTE unit is allocated four data access requests and onepartial task. The third and fourth DSTE units are only allocated threedata access requests and no partial tasks.

FIG. 42I is a diagram of another example of a distributed storage andtask processing discussed with reference to FIG. 42A where,simultaneously, a data file 1 is read and partial tasks 98 of thedistributed computing function 391 are processed. The efficiency module388 provides the efficiency information 394 that includes the desiredutilization of the DSTE units where DSTE units associated with morefavorable data access capability are identified for allocation ofallocated access requests 392. The outbound DST processing module 80allocates more read data access requests of the allocated accessrequests 392 to the identified DSTE units of the set of DSTE units whileallocating the partial task 98 to the set of DSTE units in accordancewith the desired utilization. The identified DSTE units send retrievedslices 100 to the inbound DST processing module 82. The inbound DSTprocessing module 82 decodes the retrieved slices 100 to reproduce thedata file 1. The set of DSTE units sends partial results 102 to theinbound DST processing module 82. The inbound DST processing module 82aggregates the partial results 102 to produce a result 104.

FIG. 42J is a diagram of another example of a distributed storage andtask processing discussed with reference to FIG. 42A where,simultaneously, a data file d is written to the set of DSTE units andpartial tasks 98 of the distributed computing function 391 areprocessed. The efficiency module 388 provides the efficiency information394 that includes the desired utilization of the DSTE units where DSTEunits associated with more favorable data access capability areidentified for allocation of allocated access requests 392. The outboundDST processing module 80 allocates more write data access requests ofthe allocated access requests 392 to the identified DSTE units of theset of DSTE units while allocating the partial task 98 to the set ofDSTE units in accordance with the desired utilization. Accordingly, theidentified DSTE units store encoded data slices of a plurality of setsof encoded data slices associated with data file d. The set of DSTEunits sends partial results 102 to the inbound DST processing module 82.The inbound DST processing module 82 aggregates the partial results 102to produce a result 104.

FIG. 42K is a flowchart illustrating an example of load balancing. Themethod begins at step 404 where a processing module (e.g., a distributedstorage and task client module) obtains a plurality of data accessrequests and a request to execute a distributed computing function thatincludes a plurality of partial tasks. The processing module may obtainthe data access requests and the partial tasks overlapping in time,where the data access requests are in regards with storage of a datafile and the distributed computing function is with regards to the datafile. The method continues at step 406 during the overlapping time,where the processing module establishes a desired utilization of a setof distributed storage and task execution (DSTE) units to substantiallybalance loading of the DSTE units based on per unit processing resourceutilization to processing resource capabilities.

The method continues at step 408 where the processing module establishesa desired executing efficiency and a desired data access efficiency toobtain the desired utilization of the set of DSTE units. For example,the processing module determines a read threshold when the data accessrequests includes read requests regarding reading the data file from theset of DSTE units as sets of encoded data slices. Having determined theread threshold, the processing module establishes the desired dataaccess efficiency based on the read threshold. As another example, theprocessing module determines a write threshold when the data accessrequests includes write requests regarding storing the data file as thesets of encoded data slices in the set of DSTE units. Having determinedthe write threshold, the processing module establishes the desired dataaccess efficiency based on the write threshold.

The method continues at step 410 where the processing module allocatesexecution of the partial tasks to the set of DSTE units in accordancewith the desired executing efficiency. The desired executing efficiencydistributes execution of the plurality of partial tasks among the set ofDSTE units such that, from time-to-time, differing DSTE units are notassigned execution of a partial task. The allocating may include equallyallocating partial tasks among the DSTE units. For example, theprocessing module allocates the partial tasks equally among the set ofDSTE units utilizing a pattern to provide the equal allocation, wherethe pattern indicates on a DSTE unit by DSTE unit basis of when and whennot a DSTE unit of the set of DSTE units is allocated a partial task.Alternatively, the allocating may include allocation in an imbalancedmanner. For example, the processing module allocates, in the imbalancedmanner, the partial tasks among the set of DSTE units.

The method continues at step 412 where the processing module allocatesprocessing of the data access requests to the set of DSTE units inaccordance with the desired data access efficiency, where the desireddata access efficiency distributes processing of the data accessrequests among the set of DSTE units such that, from time-to-time,differing DSTE units are not processing a data access request. Theallocation may be equally amongst the units. For example, the processingmodule equally allocates the data access requests to the set of DSTEunits utilizing a pattern to provide the equal allocation, where thepattern indicates on a DSTE unit by DSTE unit basis of when and when nota DSTE unit is allocated a data access request. Alternatively, theallocating may include allocation in the imbalanced manner. For example,the processing module allocates, in the imbalanced manner, the dataaccess requests to the set of DSTE units.

The method continues at step 414 where the processing module adjustsallocation of further partial tasks among the set of DSTE units. Forexample, in a next time interval group, the processing module increasesor decreases a number of partial tasks allocated to each DSTE unit inaccordance with a task execution performance level. The method continuesat step 416 where the processing module adjusts allocation of furtherdata access requests to the set of DSTE units. For example, in the nexttime interval group, the processing module increases or decreases anumber of data access requests allocated to each DSTE unit in accordancewith a data access execution performance level.

FIG. 43A is a schematic block diagram of another embodiment of adistributed computing system that includes the distributed storage andtask (DST) client module 34 and a set of DST execution units 36 ofFIG. 1. Each DST execution unit 36 includes a DST client module 34 and aplurality of memory devices 88. The system functions to store data asslices 422 in the memory devices 88 of each of the DST execution units36.

In an example of operation, the DST client module 34 segments the datato produce a plurality of data segments. The DST client module 34encodes each data segment using a dispersed storage error codingfunction in accordance with dispersal parameters to produce a set ofencoded data slices. The DST client module 34 determines the dispersalparameters based on one or more of a number of DST execution units 36 ofthe set of DST execution units, a sub-slicing capability of the set ofDST execution units 36, and a reliability level of the set of DSTexecution units 36. For example, the DST client module 34 determines apillar width number (e.g., number of DST execution units of the set ofDST execution units) to be seven when seven DST execution units 36 ofthe set of DST execution units 36 indicates a favorable sub-slicingcapability level.

The DST client module 34 generates a set of write slice requests 1-n 420that includes the set of encoded data slices. The DST client module 34outputs the set of write slice requests 1-n 420 to the set of DSTexecution units 36. For each DST execution unit 36, a corresponding DSTclient module 34 determines second dispersal parameters based on one ormore of a number of memory devices 88, a reliability level of the memorydevices 88, an available capacity level of the memory devices 88, and amemory device 88 loading level. For example, the DST client module 34 ofthe DST execution of 36 determines a pillar width of the seconddispersal parameters to be six when six memory devices 88 are associatedwith a favorable reliability level (e.g., above a minimum reliabilitythreshold level).

The DST client module 34 of the DST execution unit 36 encodes an encodeddata slice of a corresponding write slice request 420 using thedispersed storage error coding function in accordance with the seconddispersal parameters to produce a set of encoded data sub-slices. TheDST client module 34 of the DST execution unit 36 stores the set ofencoded data sub-slices in corresponding memory devices 88 of the DSTexecution unit 36. The method to store the data is discussed in greaterdetail with reference to FIG. 43B.

FIG. 43B is a flowchart illustrating an example of storing data. Themethod begins at step 424 where a first distributed storage and task(DST) client module selects a set of DST execution units. The selectingmay be based on one or more of a lookup, receiving identities of the setof DST execution units, and sub-slicing capabilities of the set of DSTexecution units. The method continues at step 426 where the first DSTclient module determines first dispersal parameters. The determining maybe based on one or more of a number of DST execution units of the set ofDST execution units, sub-slicing capability of the set of DST executionunits, and a reliability level of the set of DST execution units.

The method continues at step 428 where the first DST client moduleencodes a data segment using a dispersed storage error coding functionin accordance with the first dispersal parameters to produce a set ofencoded data slices. The method continues at step 430 where the firstDST client module outputs the set of encoded data slices to the set ofDST execution units. The method continues at step 432 where the firstDST client module stores storage information with regards to the set ofDST execution units. The storage information includes one or more ofidentities of the set of DST execution units, slice names correspondingto the set of encoded data slices, the first dispersal parameters, and avault identifier (ID) associated with the data segment. The storingincludes storing the storage information in at least one of a localmemory and the set of DST execution units.

The method continues at step 434 where a second DST client modulereceives an encoded data slice of the set of encoded data slices. Themethod continues at step 436 where the second DST client module selectsa set of memory devices. The selecting may be based on one or more of alookup, receiving memory device identifiers, a memory device reliabilitylevel, a memory device available storage capacity level, and a memorydevice available input/output capacity level. The method continues atstep 438 where the second DST client module determines second dispersalparameters. The determining may be based on one or more of a number ofmemory devices of the set of memory devices, the memory devicereliability level, the memory device available storage capacity level,the memory device available input/output capacity level, and the firstdispersal parameters. For example, the second DST client module selectsa pillar width to be substantially the same as the number of memorydevices of the set of memory devices.

The method continues at step 440 where the second DST client moduleencodes the encoded data slice using the dispersed storage error codingfunction in accordance with the second dispersal parameters to produce aset of encoded data sub-slices. The method continues at step 442 wherethe second DST client module stores the set of encoded data sub-slicesin the selected set of memory devices. The method continues at step 444where the second DST client module stores second storage informationwith regards to the selected set of memory devices. The storing includesgenerating the second storage information to include one or more ofidentities of the set of the selected memory devices, the slice name,the second dispersal parameters, the vault ID, and sub-slice namescorresponding to the set of encoded data sub-slices. The storing furtherincludes storing the second storage information in at least one of alocal memory, at least one of the memory devices of the set of memorydevices, and the set of DST execution units.

FIG. 44A is a schematic block diagram of another embodiment of adistributed computing system that includes the distributed storage andtask (DST) client module 34 and the set of DST execution units 36 ofFIG. 43A. The system functions to store data as shares in memory devices88 of the set of DST execution units 36. In an example of operation, theDST client module 34 segments the data to produce a plurality of datasegments. For each data segment, the DST client module 34 encodes thedata segment using a threshold based secret sharing function inaccordance with secret sharing parameters to produce a set of shares.The DST client module 34 determines the secret sharing parameters basedon one or more of a number of DST execution units 36 of the set of DSTexecution units, a sub-sharing capability of the set of DST executionunits 36, and a reliability level of the set of DST execution units 36.For example, the DST client module 34 determines a pillar width number(e.g., number of DST execution units of the set of DST execution units)to be 5 when 5 DST execution units 36 of the set of DST execution units36 indicates a favorable sub-sharing capability level.

The DST client module 34 generates a set of write share requests 1-n 446that includes the set of shares. The DST client module 34 outputs theset of write share requests 1-n 446 to the set of DST execution units36. For each DST execution unit 36, a corresponding DST client module 34of the DST execution unit 36 determines second secret sharing parametersbased on one or more of a number of memory devices, a reliability levelof the memory devices, an available capacity level of the memorydevices, and a memory device loading level. For example, thecorresponding DST client module 34 of the DST execution unit 36determines secret share threshold number of the second secret sharingparameters to be 3 when 3 memory devices are associated with a favorablereliability level.

The DST client module 34 of the DST execution unit 36 encodes a share ofa corresponding write share request 446 using the threshold based secretsharing function in accordance with the second secret sharing parametersto produce a set of sub-shares 448. The DST client module 34 of the DSTexecution unit 36 stores the set of sub-shares 448 in correspondingmemory devices 88 of the DST execution unit 36. The method to store thedata is discussed in greater detail with reference to FIG. 44B.

FIG. 44B is a flowchart illustrating another example of storing data,that includes similar steps to FIG. 43B. The method begins with step 424of FIG. 43B where a first distributed storage and task (DST) clientmodule selects a set of DST execution units. The method continues atstep 450 where the first DST client module determines first secretsharing parameters. The determining may be based on one or more of anumber of DST execution units of the set of DST execution units,sub-sharing capability of the set of DST execution units, and areliability level of the set of DST execution units.

The method continues at step 452 where the first DST client moduleencodes a data segment using a threshold based secret sharing functionin accordance with the first secret sharing parameters to produce a setof shares. The method continues at step 454 where the first DST clientmodule outputs the set of shares to the set of DST execution units. Themethod continues at step 456 where the first DST client module storesstorage information with regards to the set of DST execution units. Thestorage information includes one or more of identities of the set of DSTexecution units, share names corresponding to the set of encoded dataslices, the first secret sharing parameters, and a vault identifier (ID)associated with the data segment. The storing includes storing thestorage information in at least one of a local memory and the set of DSTexecution units.

The method continues at step 458 where a second DST client modulereceives a share of the set of shares. The method continues with step436 of FIG. 43B where the second DST client module selects a set ofmemory devices. The method continues at step 462 where the second DSTclient module determines second secret sharing parameters. Thedetermining may be based on one or more of a number of memory devices ofthe set of memory devices, the memory device reliability level, thememory device available storage capacity level, the memory deviceavailable input/output capacity level, and the first dispersalparameters. For example, the second DST client module selects athreshold number to be substantially the same as the number of memorydevices of the set of memory devices.

The method continues at step 464 where the second DST client moduleencodes the share using the threshold based secret sharing function inaccordance with the second secret sharing parameters to produce a set ofsub-shares. The method continues at step 466 where the second DST clientmodule stores the set of sub-shares in the selected set of memorydevices. The method continues at step 468 where the second DST clientmodule stores second storage information with regards to the selectedset of memory devices. The storing includes generating the secondstorage information to include one or more of identities of the set ofthe selected memory devices, a share name, the second secret sharingparameters, a vault ID, and sub-share names corresponding to the set ofsub-shares. The storing further includes storing the second storageinformation in at least one of a local memory, at least one of thememory devices of the set of memory devices, and the set of DSTexecution units.

FIG. 45A is a schematic block diagram of another embodiment of adistributed computing system that includes a distributed storage andtask client (DST) module 34, a DST execution unit 36, and one or moretemporary memory devices 470. The temporary memory devices 470 may beimplemented as one or more of a flash drive, an external magnetic diskdrive, and an external optical disk drive. The DST execution unit 36includes a DST client module 34 and one or more memory devices 88.Alternatively, the DST execution unit 36 may be implemented by at leastone of a DST processing unit, a server, and a user device. The systemfunctions to access a set of encoded data slices 1-n stored in a set ofstorage devices to emulate access of a set of DST execution units 36.The storage devices include at least one of the one or more memorydevices 88 and may include at least one of the one or more temporarymemory devices 470. Data is segmented to produce a plurality of datasegments.

In an example of operation, the DST client module 34 encodes each datasegment using a dispersed storage error coding function in accordancewith dispersal parameters to produce a corresponding set of encoded dataslices of a plurality of encoded data slices. The plurality of encodeddata slices includes the set of encoded data slices. Next, the DSTclient module 34 generates a set of slice access requests 1-n to accessthe set of encoded data slices. The set of slice access requests 1-nincludes a set of slice names corresponding to the set of encoded dataslices. The set of slice access requests 1-n includes at least one of aset of read requests and a set of write slice requests. The set of sliceaccess requests 1-n includes the set of encoded data slices when the setof slice access requests 1-n includes the set of write slice requests.The DST client module 34 outputs the set of slice access requests 1-n tothe DST execution unit 36.

The DST client module 34 of the DST execution unit 36 receives the setof slice access requests 1-n and identifies the set of storage devicesbased on at least one of the set of slice names, a storage devicecurrent level of availability indicator, an estimated storage devicefuture level of availability indicator, a storage device performancelevel indicator, and an estimated access frequency level of the set ofencoded data slices. For example, the DST client module 34 of the DSTexecution unit 36 selects the set of storage devices to include threetemporary memory devices 470 and five memory devices 88 when a pillarwidth number of the dispersal parameters is 8, a decode threshold numberof the dispersal parameters is 5, and estimated storage device futurelevel of availability indicators of the three temporary memory devices470 is favorable (e.g., likely to be available when subsequent retrievalof the set of encoded data slices is required) when the set of sliceaccess requests 1-n includes the set of write slice requests.

The DST client module 34 of the DST execution unit 36 accesses theidentified set of storage devices to facilitate the set of slice accessrequests 1-n. For example, the DST client module 34 of the DST executionunit 36 stores the set of encoded data slices in the identified set ofstorage devices when the set of slice access requests 1-n includes theset of write slice requests. As another example, the DST client module34 of the DST execution unit 36 retrieves the set of encoded data slicesfrom the identified set of storage devices when the set of slice accessrequests 1-n includes the set of read slice requests. The DST clientmodule 34 of the DST execution unit 36 generates a set of slice accessresponses 1-n to indicate at least one of status (e.g., success,failure, error code) and a result (e.g., a retrieved encoded data slice)of execution of a corresponding slice access request. Methods to accessthe identified set of storage devices to facilitate access of the set ofencoded data slices are discussed in greater detail with reference toFIGS. 45B-D.

FIG. 45B is a flowchart illustrating another example of storing data.The method begins at step 472 where a processing module (e.g., of adistributed storage and task (DST) client module of a DST executionunit) receives a set of write slice requests that includes a set ofencoded data slices for intended storage in a set of DST executionunits. The method continues at step 474 where the processing moduleselects a set of storage devices. The set of storage devices may includeone or more of memory devices and temporary memory devices. The methodcontinues at step 476 where the processing module stores the set ofencoded data slices in the set of identified storage devices. The methodcontinues at step 478 where the processing module generates a set ofwrite slice responses. For example, the processing module generates theset of write slice responses to indicate whether a corresponding encodeddata slice was successfully stored. The method continues at step 480where the processing module outputs the set of write slice responses toa requesting entity in accordance with a DST execution unit emulationapproach. The DST execution unit emulation approach includes at leastone of generating a write slice response to include one or more of awrite sequence status, a write sequence result, and an emulated DSTexecution unit identifier.

FIG. 45C is a flowchart illustrating another example of retrieving data.The method begins at step 482 where a processing module (e.g., of adistributed storage and task (DST) client module of a DST executionunit) receives at least one read slice request of a set of read slicerequests to retrieve a set of encoded data slices from a set of DSTexecution units. The method continues at step 484 where the processingmodule identifies a set of storage devices of a plurality of storagedevices associated with storage of the set of encoded data slices. Theidentifying includes at least one of performing a lookup, initiating aquery of one or more memory devices, initiating a query of one or moretemporary memory devices, and receiving a query response. The methodcontinues at step 486 where the processing module retrieves the set ofencoded data slices from the set of identified storage devices. Themethod continues at step 488 where the processing module generates a setof read slice responses that includes the set of encoded data slices.The method continues at step 490 where the processing module outputs theset of read slice responses to a requesting entity in accordance with aDST execution unit emulation approach.

FIG. 45D is a flowchart illustrating another example of rebuilding data.The method begins at step 492 where a processing module (e.g., of adistributed storage and task (DST) client module of a DST executionunit) detects a slice error associated with at least one encoded dataslice of a set of encoded data slices stored in a set of storage devicesassociated with DST execution unit emulation. The detecting includes atleast one of identifying a storage device failure associated with the atleast one encoded data slice, detecting that a storage device isunavailable (e.g., a temporary memory device is unplugged from thecomputing device), detecting slice corruption, and detecting a missingslice.

The method continues at step 494 where the processing module selects adecode threshold number of encoded data slices of the set of encodeddata slices. The decode threshold number of encoded data slices does notinclude the at least one encoded data slice. The selecting includesidentifying available encoded data slices stored in available storagedevices. The method continues at step 496 where the processing moduleretrieves the decode threshold number of encoded data slices from acorresponding decode threshold number of storage devices of the set ofstorage devices. The method continues at step 498 where the processingmodule decodes the decode threshold number of encoded data slices usinga dispersed storage error coding function to reproduce a data segment.The method continues at step 500 where the processing module encodes thedata segment using the dispersed storage error coding function toreproduce the at least one encoded data slice. Next, the processingmodule may store the reproduced at least one encoded data slice in atleast one storage device of the set of storage devices.

FIG. 46A is a schematic block diagram of an embodiment of a datacommunication system that includes a transmitting device 502 and areceiving device 504. The transmitting device 502 may be a user device12 of FIG. 1 and the receiving device 504 may be another user device 12of FIG. 1. The transmitting device 502 includes a data slice errorcontrol (EC), (e.g., or error coded) protocol layer transmit side module506, a physical layer module 508, and a processing module 510. Thereceiving device 504 includes a data slice EC protocol layer receiveside module 512, another physical layer module 508, and a processingmodule 514.

The data communication system functions to robustly communicate datafrom the transmitting device 502 to the receiving device 504. In anexample of operation, the data slice EC protocol layer transmit sidemodule 506 divides the data into data partitions, where the datapartitions include data segments. The data slice EC protocol layertransmit side module 506 forms a collection of data segments andconcurrently encodes the collection of data segments in accordance witha dispersed storage error encoding function to produce sets of encodeddata slices. Each set of encoded data slices includes a total number ofencoded data slices (e.g., a pillar width) and corresponds to a datasegment. The receiving device 504 requires a decode threshold number ofencoded data slices of the set of encoded data slices to recover thedata segment. The data slice EC protocol layer transmit side module 506generates sets of slices names for the sets of encoded data slices,where a slice name of the sets of slice names uniquely identifies anencoded data slice to a particular data segment of the collection ofdata segments.

With the sets of encoded data slices encoded, the processing module 510determines a transmit number to be initially greater than the decodethreshold number and less than the total number (e.g., based on aprevious transmit number selection, a communication path performanceindicator, a predetermination). The data slice EC protocol layertransmit side module 506 selects a transmit number of encoded dataslices from each set of encoded data slices to produce sets of transmitencoded data slices. Having produced the sets of transmit encoded dataslices, the data slice EC protocol layer transmit side module 506randomizes ordering of the sets of transmit encoded data slices toproduce a random order of encoded data slices 516.

The data slice EC protocol layer transmit side module 506 transmitsencoded data slices of the random order of encoded data slices 516. Thetransmitting includes outputting the encoded data slices 516 and slicenames and may further include at least one of the data slice EC protocollayer transmit side 506 and the processing module 510 outputtingcoordination information regarding the dispersed storage (DS) errorencoding function and an indication of the transmit number to thephysical layer module 508 of the transmitting device 502. The physicallayer module 508 of the transmitting device 502 encodes the encoded dataslices 516 (e.g., and the slice names, the DS error encoding functioncoordination information, the transmit number) using a physical layerprotocol to produce channel symbols as a robust transmission of data 518for transmission via one or more communication paths to the receivingdevice 504. The physical layer protocol may include an industry standardor proprietary approach to encode data for transmission over acommunication path (e.g., wireless, wireline) that is subject toimpairments (e.g., channel fading, dropouts, interference, symbolmixing, etc.). The physical layer protocol may include a broadcasttransmission (e.g., a simultaneous transmission to multiple recipients)and/or a unicast transmission (e.g., to one recipient).

An encoded data slice error rate corresponds to a number of datasegments per data partition (e.g., D) and the transmit number (e.g.,k<t<n; where n=total number, k=decode threshold number) minus the decodethreshold in accordance with an expression: maximum number of contiguousslices that may be dropped=D*(t−k). For example, eight contiguousencoded data slices 516 may be dropped from the robust transmission ofdata 518 without affecting the transmission of the data when a number ofdata partitions is 4, the transmission number is 5 and the decodethreshold is 3.

With the robust transmission of data 518 transmitted from thetransmitting device 502 to the receiving device 504, the physical layermodule 508 of the receiving device 504 decodes the channel symbols toproduce received encoded data slices 520 of the random order of encodeddata slices (e.g., including slice names, the transmit number, the DSerror encoding function coordination information). The physical layermodule 508 of the receiving device 504 utilizes the physical layerprotocol to decode the channel symbols to reproduce the encoded dataslices 520. From time to time, channel impairments may overwhelm acapability level of the physical layer protocol to correct errors. Whenoverwhelmed, the reproduced encoded data slices 520 may not include eachof the encoded data slices 516 that were transmitted from thetransmitting device 502.

The data slice EC protocol layer receive side module 512 receives theencoded data slices 520 and interprets the corresponding slice names tode-randomize the random order of encoded data slices into sets oftransmit encoded data slices. As a specific example, the data slice ECprotocol layer receive side module 512 interprets, for an encoded dataslice of the received encoded data slices 520, a corresponding slicename to identify a segment identifier that ties the encoded data sliceto one of the collection of data segments, a data object identifier thatties the encoded data slice to the data, and a slice identifier thatuniquely identifies the encoded data slice in the set of encoded dataslices.

With the received encoded data slices 520 de-randomized, the data sliceEC protocol layer receive side module 512, on a set by set basis andusing the dispersed storage error encoding function, determines whetherthe decode threshold number of encoded data slices of a set of transmitencoded data slices have been received (e.g., decodable if so). When thedecode threshold number of encoded data slices have not yet beenreceived, the data slice EC protocol layer receive side module 512determines whether a sufficient number of encoded data slices of the setof transmit encoded data slices are still to be received. As a specificexample, the data slice EC protocol layer receive side module 512identifies encoded data slices of the set of transmit encoded dataslices that have been successfully received, determines how many moreencoded data slices are to be received based on the transmit number anda current order position in the serially receiving the random order ofencoded data slices, and when a sum of the number of encoded data slicesthat have been successfully received and a number of the more encodeddata slices to be received is equal to or greater than the decodethreshold number, the data slice EC protocol layer receive side module512 indicates that the sufficient number of encoded data slices arestill to be received.

Having determined whether the sufficient number of encoded data slicesare still to be received, the data slice EC protocol layer receive sidemodule 512 waits until the decode threshold number of encoded dataslices are received when the sufficient number of encoded data slicesare still to be received. Alternatively, when the data slice EC protocollayer receive side module 512 indicates that less than the sufficientnumber of encoded data slices are still to be received, the processingmodule 514 sends a feedback message 522 that requests one or moreencoded data slices of the set of encoded data slices to be transmitted(e.g., re-send missed encoded data slices, send other encoded dataslices). The feedback message 522 may include a request for one or moreencoded data slices of the set of encoded data slices and slice names ofencoded data slices that have been successfully received. The physicallayer module 508 of the receiving device 504 encodes the feedback 522using the physical layer protocol to output a transmission of feedback524 to the transmitting device 502.

The physical layer module 508 of the transmitting device 502 receivesthe transmission of feedback 524 from the receiving device 504 (e.g., arecipient of the transmit encoded data slices 516) and applies thephysical layer protocol on the transmission of feedback 524 to recapturethe feedback. The processing module 510 interprets the feedback 522 todetermine, for a data segment, that at least one more encoded data sliceof the set of encoded data slices of the data segment is to betransmitted to the receiving device 504 such that the receiving device504 has the decode threshold number of encoded data slices to recoverthe data segment. The processing module 510 identifies one or moreencoded data slices from a remaining subset of encoded data slicescorresponding to the encoded data slices between the transmit number andthe total number (e.g., slice is not sent yet, alternatively resend aslice that was missed). The processing module 510 interrupts thetransmitting of the encoded data slices of the random order of encodeddata slices 516 to send the one more encoded data slices to thereceiving device 504 (e.g., inserting and/or appending).

The receiving device 504 may miss an unacceptable number of receivedencoded data slices 520 with regards to parameters affecting the encodeddata slice error rate. The processing module 510 interprets the feedback522 to determine whether an adjustment should be made regarding therobust transmission of data 518. For example, the processing module 510determines that the adjustment should be made when a planned transmitnumber of encoded data slices for the set of encoded data slices is notenough due to missed received encoded data slices 520. For instance, theprocessing module 510 determines that the adjustment should be made whenreceiving feedback at a rate higher than a high feedback generation ratethreshold. When the adjustment should be made, the processing module 510determines at least one of increasing or decreasing the number of datasegments per data partition, and increasing or decreasing the transmitnumber. For instance, the processing module 510 determines to increasethe number of data segments per data partition when the encoded dataslice error rate is higher than a maximum error rate threshold asindicated by identified missing encoded data slices. In anotherinstance, the processing module 510 determines to decrease the transmitnumber when the encoded data slice error rate is less than a minimumerror rate threshold.

When the decode threshold number of encoded data slices are received,the data slice EC protocol layer receive side module 512 decodes thethreshold number of encoded data slices to recapture a correspondingdata segment of the collection of data segments and may send a feedbackmessage 522 requesting that one or more encoded data slices not be sent(e.g., since the decode threshold number of encoded data slices havealready been received). The data slice EC protocol layer receive sidemodule 512 recaptures collections of data segments to recover the dataportions and combines the data portions to reproduce the data.

FIG. 46B is a schematic block diagram of another embodiment of a datacommunication system that includes the transmitting device 502 and aplurality of the receiving devices 504 of FIG. 46A. The transmittingdevice 502 transmits the encoded data slices of the random order ofencoded data slices 516 as at least one of individual unicasttransmissions of the robust transmission of data 518 to each receivingdevice 504 and as a broadcast of a common robust transmission of data518 simultaneously to all of the receiving devices 504. Each receivingdevice 504 receives the robust transmission of data 518, receives theencoded data slices 520 of the random order of encoded data slices 516,and determines whether to issue a corresponding transmission of feedback524 based on receiving and decoding the received encoded data slices520. For example, a first receiving device 504 issues the correspondingtransmission of feedback 524 indicating that additional encoded dataslices are required for a set of encoded data slices and a secondreceiving device 504 does not issue another corresponding transmissionof feedback 524 when receiving enough encoded data slices for the set ofencoded data slices.

In response to receiving one or more transmissions of feedback 524, thetransmitting device 502 may interrupt the robust transmission of data518 to include additional encoded data slices of the encoded data slices516. The transmitting device 502 may send the additional encoded dataslices to a corresponding receiving device 504 requiring additionalencoded data slices as a unicast message within the robust transmissionof data 518 being transmitted to the corresponding receiving device 504.Alternatively, the transmitting device 502 may send the additionalencoded data slices to all receiving devices 504 as a broadcast messagewhen at least one of the receiving devices 504 requires the additionalencoded data slices.

FIG. 46C is a schematic block diagram of an embodiment of the data sliceerror coded (EC) protocol layer transmit side module 506 and theprocessing module 510 of FIG. 46A, where the data slice EC protocollayer transmit side module 506 includes the data partitioning module 110of FIG. 4, a data segmenting module 526, a segment buffer 528, a set ofdispersed storage (DS) error encoding modules 112 of FIG. 4, a slicebuffer 530, a set of subset selection modules 532, and a transmit bufferand multiplexer (MUX) module 534.

In an example of operation, the data partitioning module 110 uses apartitioning scheme to partition data 536 into a set of data partitions538. For example, the data partitioning module 110 partitions the datainto a set of a partition number (e.g., D) of equally sized datapartitions 538. The data segmenting module 526 uses a segmenting schemeto segment the data partitions 538 to produce segments 540 andtemporarily stores the segments 540 in the segment buffer 528 to providea collection of data segments 542 for each of the DS error encodingmodules 112. For example, the data segmenting module 526 segments thedata partitions 538 to produce a first collection of data segments thatincludes data segments of one data partition. As another example, thedata segmenting module 526 segments the data partitions 538 to producefirst data segments of the data segments of a given number (e.g., D) ofdata partitions 538. As yet another example, the data segmenting module526 segments the data partitions 538 to produce second data segments ofthe data segments of the given number of data partitions 538. As a stillfurther example, the data segmenting module 526 segments the datapartitions 538 to produce a data segment of a given number of datasegments of the data segments of the given number of data partitions.

FIGS. 46D-G illustrate various segmenting schemes to provide thecollection of data segments 542 from the segment buffer 528 to the setof DS error encoding modules 112. In particular, FIG. 46D illustrates anexample where segments 540 from the data segmenting module 526 includesfour data segments for each of four data partitions. The segment buffer528 provides segment buffering 552 to output for collections of datasegments where each collection includes the four data segments of acommon data partition. For example, a segment collection 1 includes datasegments 1-4 associated with data partition 1. FIG. 46E illustratesanother example where the segment buffer 528 provides the segmentbuffering 552 output for the collections of data segments where eachcollection includes a common segment number of each of the datapartitions. For example, the segment collection 1 includes four datasegment 4 s associated with each data partition 1-4. FIG. 46Fillustrates another example where the segment buffer 528 provides thesegment buffering 552 output for the collections of data segments whereeach collection includes a pseudorandom selection where the collectionincludes unique data segment numbers from unique data. For example, thesegment collection 1 includes data segments associated with differentdata segment numbers from four different data partitions. FIG. 46Gillustrates another example where the segment buffer 528 provides thesegment buffering 552 output for the collections of data segments whereeach collection includes a random selection where the collectionincludes any data segment number from any data partition. For example,the segment collection 1 includes some common segment numbers anduncommon segment numbers of some common and uncommon data partitions.

Returning to the discussion of FIG. 46C, each of the DS error encodingmodules 112 concurrently encodes an associated collection of datasegments 542 in accordance with a dispersed storage error encodingfunction to produce sets of encoded data slices. Each set of encodeddata slices includes a total number (e.g., n) of encoded data slices andcorresponds to a data segment of the collection of data segments. Adecode threshold number (e.g., k) of encoded data slices of the set ofencoded data slices is required to recover the corresponding datasegment. Each DS error encoding module 112 generates sets of slicesnames for associated sets of encoded data slices, where a slice nameuniquely identifies an encoded data slice to a particular data segmentof the collection of data segments. The set of DS error encoding modules112 stores the sets of encoded data slices and sets of slice names inthe slice buffer 530.

The processing module 510 determines a transmit number 544 to beinitially greater than the decode threshold number and less than thetotal number. The set of subset selection modules 532 selects a transmitnumber of encoded data slices from each set of encoded data slices fromthe slice buffer 530 to produce sets of transmit encoded data slices548. The processing module 510 coordinates with a recipient (e.g., thereceiving device 504 of FIG. 46A) regarding the dispersed storage errorencoding function and sends an indication of the transmit number 544 torecipient.

FIG. 46H illustrates one of many possible examples of selecting thetransmit number of encoded data slices from the sets of encoded dataslices where the sets of encoded data slices includes encoded dataslices of a first collection of four data segments 1-4 where each datasegment is encoded to produce six encoded data slices (EDS). Forexample, a fourth set of encoded data slices includes encoded dataslices 1-6 of a fourth data segment of the first data segmentcollection. Each encoded data slice is stored in the slice buffer 530along with a corresponding slice name. The slice name may be interpretedto identify a segment identifier that ties the encoded data slice to oneof the collection of data segments, a data object identifier that tiesthe encoded data slice to the data, and a slice identifier that uniquelyidentifies the encoded data slice in the set of encoded data slices. Theselecting of the transmit number of encoded data slices from each set ofencoded data slices includes four encoded data slices for each transmitencoded data slice set of four transmit encoded data slices sets 1-4 asan output of subset selections 554. Each transmit encoded data slice setmay include same or different slice numbers per set. For example, atransmit encoded data slices set 1 includes a first four encoded dataslices 1-4 of the encoded data slice set 1 for segment 1 of data segmentcollection 1. As another example, a transmit encoded data slices set 3includes encoded data slices 1-2 and 5-6 of the encoded data slice set 3for segment 3 of data segment collection 1.

Returning to the discussion of FIG. 46C, the transmit buffer and MUXmodule 534 randomizes ordering of the sets of transmit encoded dataslices 548 to produce a random order of encoded data slices 516 inaccordance with an ordering pattern 550 to establish a transmit order556. The transmit buffer and MUX module 534 transmits encoded dataslices of the random order of encoded data slices 516 and sends, in anorder corresponding to the randomized ordering, the sets of slice nameswith the random order of encoded data slices. FIGS. 46I-J illustrate anexample of the transmit order 556. In the examples, the output of subsetselections 554 that includes the sets of transmit encoded data slices ofFIG. 46H are to be transmitted to the one or more recipients inaccordance with the ordering pattern 550 and transmit order 556. Inparticular, FIG. 46I illustrates an example where the transmit order 556includes sending encoded data slices of sequential segments 1-4 in arepetitive pattern. For instance, slice 4 of segment 1 is sent followedby a slice 4 of segment 2, followed by slice 6 of segment 3, followed bya slice 6 of segment 4, followed by slice 3 of segment 1, etc. Asanother example, FIG. 46J illustrates an example where the transmitorder 556 includes sending encoded data slices using a random pattern.For instance, slice 4 of segment 1 is sent, followed by slice 4 segment2, followed by slice 3 of segment 1, followed by slice 3 a segment 2,etc. Many other ordering patterns 550 and resulting transmit orders 556are possible.

Returning to the discussion of FIG. 46C, the processing module 510receives feedback 522 from one or more recipients of the random order ofencoded data slices 516. The feedback 522 is in regards to one or moreof reception and non-reception of sent encoded data slices and a requestfor more encoded data slices beyond a planned transmit encoded dataslice set. Examples of generation of the feedback 522 will be discussedin greater detail with reference to FIGS. L-O. The processing module 510interprets the feedback 522 to determine whether to adjust parameters ofrobust transmission of the encoded data slices and/or to send more thanplanned encoded data slices to the one or more recipients. For example,the processing module 510 interprets the feedback 522 to determinewhether an adjustment should be made regarding the robust transmission(e.g., adjust when encoded data slice error rate too high or too low).When the adjustment should be made, the processing module 510 determinesat least one of increasing or decreasing the number of data segments perdata partition and increasing or decreasing the transmit number.

In an example of interpreting the feedback 522 to determine whether tosend more than the planned encoded data slices to the one or morerecipients, the processing module 510 interprets the feedback 522 todetermine, for a data segment of the collection of data segments, thatat least one more encoded data slice of the set of encoded data slicesof the data segment is to be transmitted to the recipient such that therecipient has the decode threshold number of encoded data slices torecover the data segment. Next, the processing module 510 identifiesanother one more encoded data slices from a remaining subset of encodeddata slices corresponding to the encoded data slices between thetransmit number and the total number. Having identified the other one ormore encoded data slices, the processing module 510 issues an interrupt552 to the transmit buffer and MUX module 534 to interrupt thetransmitting of the encoded data slices of the random order of encodeddata slices 516 to send the other one more encoded data slices.

In another example of interpreting the feedback 522 to determine whetherto send more than the planned encoded data slices to the one or morerecipients, the processing module 510 interprets the feedback 522 todetermine, for the data segment, whether the recipient has received thedecode threshold number of encoded data slices for the data segment andwhether another encoded data slice of the transmit number of encodeddata slices for the data segment remain to be transmitted. When therecipient has received the decode threshold number of encoded dataslices for the data segment and the other encoded data slice of thetransmit number of encoded data slices remains to be transmitted, theprocessing module facilitates removal of the other encoded data slicefrom the random order of encoded data slices 516 (e.g., issues anotherinterrupt 552 to the transmit buffer and MUX module 534 with a slicename corresponding to the other encoded data slice for removal).

In yet another example of interpreting the feedback 522 to determinewhether to send more than the planned encoded data slices to the one ormore recipients, the processing module 510 receives, from the recipient,feedback regarding accurate receipt of encoded data slices correspondingto the data segment (e.g., which were received and/or not received).Next, the processing module 510 interprets the feedback 522 todetermine, for the data segment, whether the recipient will receive thedecode threshold number of encoded data slices for the data segmentbased on a remaining number of encoded data slices of the transmitnumber of encoded data slices for the data segment that have not beentransmitted. When the recipient will not receive the decode thresholdnumber of encoded data slices for the data segment based on theremaining number of encoded data slices of the transmit number ofencoded data slices for the data segment, the processing module 510identifies another encoded data slice from a remaining subset of encodeddata slices corresponding to the encoded data slices between thetransmit number and the total number. The processing module 510 issuesanother interrupt 552 that includes identity of the other encoded dataslice such that the transmit buffer and MUX module 534 adds the otherencoded data slice to the random order of encoded data slices 516.

FIG. 46K is a schematic block diagram of an embodiment of the data sliceerror coded (EC) protocol layer receive side 512 and the processingmodule 514 of FIG. 46A, where the data slice EC protocol layer receiveside module 512 includes the data de-partitioning module 184 of FIG. 13,a data de-segmenting module 558, a de-segment buffer 560, a set ofdispersed storage (DS) error decoding modules 182 of FIG. 13, a set ofthreshold buffer modules 1-D, and a received buffer and a de-multiplexer(deMUX) module 561.

In an example of operation, the receive buffer and deMUX module 561receives encoded data slices 520 of a random order of encoded dataslices, where each encoded data slice has a unique slice name. Thereceive buffer and deMUX module 561 interprets slice names tode-randomize the random order of encoded data slices in accordance withan ordering pattered 550 into sets of transmit encoded data slices,where the sets of transmit encoded data slices corresponds to sets ofencoded data slices. The ordering pattern 550 may be obtained by atleast one of receiving the ordering pattern 550 from a sending entity,utilizing a predetermination, and determining the ordering pattern 550based on interpreting the slice names.

The plurality sets of encoded data slices are dispersed storage errorencoded versions of a collection of data segments of data portions ofdata. Each set of transmit encoded data slices includes a transmitnumber 544 of encoded data slices of a total number of encoded dataslices of a corresponding set of encoded data slices. As a specificexample of interpreting, the receive buffer and deMUX module 561interprets, for an encoded data slice, a corresponding slice name toidentify a segment identifier that ties the encoded data slice to one ofthe collection of data segments, a data object identifier that ties theencoded data slice to the data, and a slice identifier that uniquelyidentifies the encoded data slice in the set of encoded data slices. Thereceive buffer and deMUX module 561 outputs receiver buffer status 564to the processing module 514, where the status 564 includes anindication of the slice names.

Each of the threshold buffers 1-D attempts to collect a decode thresholdnumber 562 of encoded data slices 546 of sets of encoded data slicesfrom the receive buffer and deMUX module 561 as the random order ofencoded data slices 520 is received in accordance with a randomreception order 568. The threshold buffers 1-D each provides a bufferstatus 566 to the processing module 514 indicating whether the decodethreshold number 562 of encoded data slices 546 has been collected.FIGS. 46L-N illustrates examples of the random reception order 568 wherefour transmit encoded data slice sets 1-4 are transmitted with thetransmit order 556 of FIG. 46I. In particular, FIG. 46L illustrates anexample when all encoded data slices of the four transmit encoded dataslice sets 1-4 are received with no errors. The decode threshold numberof encoded data slices per set of the transmit encoded data slice setshas been received after receiving a third column of the four columns(e.g., when the decode threshold number is three). As such, transmissionof additional encoded data slices for each of the transmit encoded dataslice sets is not required. Feedback may be provided indicating thatsufficient slices have been received.

As another example, FIG. 46M illustrates an example when a maximumnumber of contiguous encoded data slices are not received for the setsof transmit encoded data slices and each of the transmit encoded dataslice sets are decodable when waiting for all of the encoded data slicesof the transmit encoded data slice sets 1-4 to be received. As yetanother example, FIG. 46N illustrates an example when too many encodeddata slices are not received preventing decoding of at least onecorresponding data segment. Interpretation of the received encoded dataslices after two encoded data slices of the third transmit encoded dataslice set were not received indicates that a sufficient number ofencoded data slices for transmit encoded data slices set 3 will not bereceived from the transmit number of encoded data slices and at leastone more encoded data slice is required.

Returning to the discussion of FIG. 46K, the processing module 514, on aset by set basis and in accordance with a dispersed storage errorencoding function, determines whether the decode threshold number ofencoded data slices of a set of transmit encoded data slices of the setsof transmit encoded data slices have been received based on one or moreof the receiver buffer status 564 and the buffer status 566. When thedecode threshold number of encoded data slices have not yet beenreceived, the processing module 514 determines whether a sufficientnumber of encoded data slices of the set of transmit encoded data slicesare still to be received (e.g., more slices should be received of thetransmit number of slices). As a specific example, the processing module514 identifies encoded data slices of the set of transmit encoded dataslices that have been successfully received and determines how many moreencoded data slices are to be received based on the transmit number anda current order position in the serially receiving the random order ofencoded data slices. When a sum of the number of encoded data slicesthat have been successfully received and a number of the more encodeddata slices to be received is equal to or greater than the decodethreshold number, the processing module 514 indicates that thesufficient number of encoded data slices are still to be received.

When the sufficient number of encoded data slices are still to bereceived, the processing module 514 waits until the decode thresholdnumber of encoded data slices are received. When less than thesufficient number of encoded data slices are still to be received, theprocessing module 514 sends a feedback message 522 that requests one ormore encoded data slices of the set of encoded data slices to betransmitted. Alternatively, or in addition to, the processing module 514sends the feedback message 522 that includes a request for one or moreencoded data slices of the set of encoded data slices and slice names ofencoded data slices that have been successfully received.

Once each of the threshold buffers 1-D has a decode threshold number ofencoded data slices for each corresponding set of encoded data slices,each of the corresponding DS error decoding modules 182 decodes thedecode threshold number of encoded data slices to recapture acorresponding data segment of the collection of data segments. Inaddition, the processing module 514 may determine whether one or moreencoded data slices of the set of transmit encoded data slices are stillto be received (e.g., now unnecessary). When the one or more encodeddata slices are still to be received, the processing module 514 sendsanother feedback message 522 requesting that the one or more encodeddata slices not be sent.

Each DS error decoding module 182 outputs collections of data segments542 to the de-segment buffer 560. Each of the de-segment buffer 560, thedata de-segmenting module 558, and the data de-partitioning module 184perform opposite functions as compared to corresponding counterpartsincluding the segment buffer 528, the data segmenting module 526, andthe data partitioning module 110 of FIG. 46C. For example, the datade-segmenting module 558 de-segments data segments 540 to recover thedata partitions 538 (e.g., data portions). The data de-partitioningmodule 184 combines the data partitions to reproduce data 536.

FIG. 46O is a diagram illustrating an example of interrupt transmitordering of encoded data slices that includes the transmitting device502 and the receiving device 504 of FIG. 46A. In an example ofoperation, the transmitting device 502 sends the robust transmission ofdata 518 to the receiving device 504 that includes the transmit encodeddata slices sets 1-4 transmitted in accordance with the transmit order556 of FIG. 46I. The receiving device 502 determines that two encodeddata slices of transmit encoded data slices set 3 are not received andissues a transmission of feedback 524 that includes feedback withregards to the two encoded data slices that were not received. Thetransmitting device 502 receives the feedback and determines how manyand which encoded data slices to send to the receiving device 504. Forinstance, the transmitting device 502 identifies encoded data slice 4 ofthe set of encoded data slices associated with the transmit encoded dataslices set 3.

The transmitting device 502 may interrupt the robust transmission ofdata 518 at any time. In this example, the transmitting device 502 sendsan interrupt transmission of data 570 to the receiving device 504, wherethe interrupt transmission of data 570 includes the encoded data slice4. For instance, the transmitting device 502 interrupts the robusttransmission of data 518 after completion of sending of a second columnof the sets of transmit encoded data slices to send encoded data slice 4of the set of encoded data slices associated with the transmit encodeddata slices set 3. In another instance, the transmitting device 502sends the encoded data slice 4 after sending the transmit number ofencoded data slices for each transmit encoded data slices set.

FIG. 46P is a flowchart illustrating an example of encoding data for arobust transmission of the data to a recipient. The method begins atstep 572 where a processing module (e.g., of a distributed storage andtask client module) divides the data for transmission into datapartitions, where a data partition includes data segments. For acollection of data segments of the data segments from one or more datapartitions, the method continues at step 574 where the processing moduleconcurrently encodes the collection of data segments using a dispersedstorage error encoding function to produce sets of encoded data slices.The collection of data segments includes one of: the data segments ofone of the data partitions, first data segments of the data segments ofa given number of data partitions, second data segments of the datasegments of the given number of data partitions, and a data segment of agiven number of data segments of the given number of data partitions.Each set of encoded data slices includes a total number of encoded dataslices and corresponds to a data segment of the collection of datasegments. A decode threshold number of encoded data slices of the set ofencoded data slices is required to recover the corresponding datasegment.

The method continues at step 576 where the processing module coordinateswith the recipient regarding the dispersed storage error encodingfunction. As a specific example, the processing module issues dispersedstorage error encoding function information (e.g., function identifier,dispersal parameters) to the recipient. As another specific example, therecipient requests the dispersed storage error coding functioninformation. The method continues at step 578 where the processingmodule generates sets of slices names for the sets of encoded dataslices, where each slice name uniquely identifies an encoded data sliceto a particular data segment of the collection of data segments. Themethod continues at step 580 where the processing module determines atransmit number to be initially greater than the decode threshold numberand less than the total number. The method continues at step 582 wherethe processing module sends an indication of the transmit number to therecipient.

The method continues at step 584 where the processing module selects atransmit number of encoded data slices from each of the sets of encodeddata slices to produce sets of transmit encoded data slices. The methodcontinues at step 586 where the processing module randomizes ordering ofthe plurality of sets of transmit encoded data slices to produce arandom order of encoded data slices. The method continues at step 588where the processing module transmits encoded data slices of the randomorder of encoded data slices, where an encoded data slice error ratecorresponds to a number of data segments per data partition and thetransmit number minus the decode threshold. The method continues at step590 where the processing module sends, in an order corresponding to therandomized ordering, the sets of slice names with the random order ofencoded data slices.

The method continues at step 592 where the processing module receivesfeedback from the recipient of the transmit encoded data slices. As aspecific example, the processing module receives, from the recipient,feedback regarding accurate receipt of encoded data slices correspondingto a data segment of the collection of data segments (e.g., slice namesof received encoded data slices, slice names of non-received encodeddata slices). The method continues at step 594 where the processingmodule interprets the feedback to determine whether an adjustment shouldbe made regarding the robust transmission. For example, the processingmodule determines to adjust parameters of the robust transmission whenthe encoded data slice error rate is greater than a maximum error ratethreshold. The method branches to step 598 when the processing moduledetermines not to adjust the robust transmission. The method continuesto step 596 when the processing module determines to adjust the robusttransmission. The method continues at step 596 where the processingmodule determines at least one of increasing or decreasing the number ofdata segments per data partition and increasing or decreasing thetransmit number.

The method continues at step 598 where the processing module interpretsthe feedback to determine whether to add or remove encoded data slicesof the robust transmission. As a specific example of interpreting thefeedback, the processing module interprets the feedback to determine,for the data segment, whether the recipient has received the decodethreshold number of encoded data slices for the data segment and whetherat least one encoded data slice of the transmit number of encoded dataslices for the data segment remains to be transmitted. When therecipient has received the decode threshold number of encoded dataslices for the data segment and the at least one encoded data slice ofthe transmit number of encoded data slices remains to be transmitted,the method branches to step 600 to remove encoded data slices of therobust transmission. As another specific example of interpreting thefeedback, the processing module interprets the feedback to determine,for a data segment of the collection of data segments, that at least onemore encoded data slice of the set of encoded data slices of the datasegment is to be transmitted to the recipient such that the recipienthas the decode threshold number of encoded data slices to recover thedata segment. When the at least one more encoded data slice of the setof encoded data slices of the data segment is to be transmitted to therecipient such that the recipient has the decode threshold number ofencoded data slices to recover the data segment, the method branches tostep 602 to add encoded data slices. As another specific example ofinterpreting the feedback, the processing module interprets the feedbackto determine, for the data segment, whether the recipient will receivethe decode threshold number of encoded data slices for the data segmentbased on a remaining number of encoded data slice of the transmit numberof encoded data slices for the data segment that have not beentransmitted. When the recipient will not receive the decode thresholdnumber of encoded data slices for the data segment based on theremaining number of encoded data slices of the transmit number ofencoded data slices for the data segment, the method branches to step604 to add encoded data slices.

When the recipient has received the decode threshold number of encodeddata slices for the data segment and the at least one encoded data sliceof the transmit number of encoded data slices remains to be transmitted,the method continues at step 600 where the processing module removes theat least one encoded data slice from the random order of encoded dataslices. When the at least one more encoded data slice of the set ofencoded data slices of the data segment is to be transmitted to therecipient such that the recipient has the decode threshold number ofencoded data slices to recover the data segment, the method continues atstep 602 where the processing module identifies the at least one moreencoded data slice from a remaining subset of encoded data slicescorresponding to the encoded data slices between the transmit number andthe total number. Next, the processing module interrupts thetransmitting of the encoded data slices of the random order of encodeddata slices to send the at least one more encoded data slice. When therecipient will not receive the decode threshold number of encoded dataslices for the data segment based on the remaining number of encodeddata slices of the transmit number of encoded data slices for the datasegment, the method continues at step 604 where the processing moduleidentifies the at least one more encoded data slice from the remainingsubset of encoded data slices corresponding to the encoded data slicesbetween the transmit number and the total number. Next, the processingmodule adds the at least one more encoded data slice to the random orderof encoded data slices.

FIG. 46Q is a flowchart illustrating an example of decoding data forrobust reception of the data. The method begins at step 606 where aprocessing module (e.g., of a distributed storage and task (DST) clientmodule) receives encoded data slices of a random order of encoded dataslices. Each encoded data slice of the random order of encoded dataslices has a unique slice name. An encoded data slice error ratecorresponds to a number of data segments per data partition and atransmit number minus a decode threshold number. The method continues atstep 608 where the processing module interprets slice names tode-randomize the random order of encoded data slices into sets oftransmit encoded data slices. The sets of transmit encoded data slicescorresponds to sets encoded data slices, where the sets of encoded dataslices is a dispersed storage error encoded version of a collection ofdata segments of a data portion of data portions of the data. Each setof transmit encoded data slices includes the transmit number of encodeddata slices of a total number of encoded data slices of a correspondingset of encoded data slices.

As a specific example, the processing module interprets, for an encodeddata slice, a corresponding slice name to identify a segment identifierthat ties the encoded data slice to one of the collection of datasegments. As another specific example, the processing module interpretsthe corresponding slice name to identify a data object identifier thatties the encoded data slice to the data. As yet another specificexample, the processing module interprets the corresponding slice nameto identify a slice identifier that uniquely identifies the encoded dataslice in the set of encoded data slices.

The method continues at step 610, where the processing module, on a setby set basis and in accordance with a dispersed storage error encodingfunction (e.g., using the decode threshold number), determines whetherthe decode threshold number of encoded data slices of a set of transmitencoded data slices of the sets of transmit encoded data slices havebeen received. The method branches to step 616 when the decode thresholdnumber of encoded data slices have not been received. The methodcontinues to step 612 when the decode threshold number of encoded dataslices have been received. The method continues at step 612 where theprocessing module determines whether one or more encoded data slices ofthe set of transmit encoded data slices are still to be received whenthe decode threshold number of encoded data slices have been received(e.g., based on interpretation of a transmit ordering pattern and thedecode threshold number). When the one or more encoded data slices arestill to be received, the method continues at step 614 where theprocessing module sends a feedback message requesting that the one ormore encoded data slices not be sent. The method branches to step 624.

When the decode threshold number of encoded data slices have not yetbeen received, the method continues at step 616 where the processingmodule determines whether a sufficient number of encoded data slices ofthe set of transmit encoded data slices are still to be received. As aspecific example, the processing module identifies encoded data slicesof the set of transmit encoded data slices that have been successfullyreceived and determines how many more encoded data slices are to bereceived based on the transmit number and a current order position inserially receiving the random order of encoded data slices. When theprocessing module determines that a sum of the number of encoded dataslices that have been successfully received and a number of the moreencoded data slices to be received is equal to or greater than thedecode threshold number, the processing module indicates that thesufficient number of encoded data slices are still to be received. Themethod branches to step 622 where the processing module determines thatless than the sufficient number of encoded data slices are still to bereceived. The method continues to step 618 when the sufficient number ofencoded data slices are still to be received. The method continues atstep 618 where the processing module waits until the decode thresholdnumber of encoded data slices are received when the sufficient number ofencoded data slices are still to be received. When the decode thresholdnumber of encoded data slices are received, the method continues at step620 where the processing module decodes the decode threshold number ofencoded data slices to recapture a corresponding data segment of thecollection of data segments. The method branches to step 624.

When less than the sufficient number of encoded data slices are still tobe received, the method continues at step 622 where the processingmodule sends a feedback message that requests one or more encoded dataslices of the set of encoded data slices to be transmitted.Alternatively, the processing module sends a feedback message thatincludes a request for the one or more encoded data slices of the set ofencoded data slices and slice names of encoded data slices that havebeen successfully received.

The method continues at step 624 where the processing module recoversthe data portions. For example, the processing module aggregatescorresponding collections of data segments to reproduce each dataportion. The method continues at step 626 where the processing modulecombines the data portions to reproduce the data.

FIG. 47A is a schematic block diagram of another embodiment of adistributed storage and task (DST) execution unit 36 that includes aplurality of the interfaces 169, a plurality of the processing modules84, a plurality of the memories 88, a plurality of the distributed task(DT) execution modules 90, and a plurality of the DST client modules 34of FIGS. 3 and 11. The DST execution unit 36 receives, via at least oneinterface 169, requests to execute a plurality of tasks. A task of theplurality of tasks includes at least one of rebuilding data, balancingdata, migrating data, accessing data, writing data, reading data,determining a result, verifying consistency of data, scanning for lostslices, performing rebuilding operations, encrypting slices, decryptingslices, calculating an integrity value, comparing the calculatedintegrity value to a received integrity value, and processing adistributed computing job.

At least one processing module 84 determines a priority level associatedwith the task. The determining may be based on one or more of a taskprioritization scheme, a task type, an estimated duration of taskcompletion, a requesting entity identifier (ID), a task executionresource performance level, and prioritization guidance (e.g., allowableto increase priority, allowable to decrease priority). The determiningof the priority level associated with the task may be performed at anytime including initial receipt of the task by the DST execution unit 36and any subsequent time period thereafter up to when the task isexecuted. For example, the processing module 84 lowers the prioritylevel associated with the task during execution of the task when thetask execution resource performance level indicates that the taskexecution is very favorable.

At least one of the processing module 84 and a DT execution module 90assigns resources of the DST execution unit 36 to execute the task inaccordance with the priority level of the task. For example, theprocessing module 84 assigns a higher than average number of resourcesto the task when the priority level is higher than average. Theassigning may be performed at any time during execution of the tasksincluding an initial assignment and a subsequent assignment during taskexecution. The resources for execution of the task include one or moreof allocated memory 88, processing threads, number of processingmodules, amount of processing utilization, number of DT executionmodules 90, number of DST client modules 34, amount of memory 88, andamount of memory bandwidth. The method of operation to assigning thepriority level and to assign the resources is discussed in greaterdetail with reference to FIG. 47B.

FIG. 47B is a flowchart illustrating an example of prioritizing tasks.The method begins at step 630 where a processing module (e.g., of adistributed storage and task (DST) execution unit) identifies requiredresources for one or more tasks of a plurality of pending tasks. Theidentifying is based on one or more of a lookup, receiving a resourceidentifier, accessing a record of a previous resource assignment, and atable of required resources and tasks. The method continues at step 632where the processing module determines resource availability informationfor one or more resources of a plurality of resources. The determiningmay be based on one or more of a lookup, initiating a query, receivingthe availability information, accessing a historical record of resourceavailability, and initiating a test.

The method continues at step 634 where the processing module determinesa task priority level for each of the one more tasks of the plurality ofpending tasks in accordance with a task prioritization scheme. The taskprioritization scheme may indicate which types of tasks are to beprioritized higher or lower than other tasks. The method continues atstep 636 where the processing module facilitates execution of the onemore tasks of the plurality of pending tasks in accordance with the taskpriority level for each of the one or more tasks of the plurality ofpending tasks and a task priority level of each other task of theplurality of pending tasks. For example, the processing module executestasks in order of priority and time received when the tasks include acommon priority level.

The method continues at step 638 where the processing module determinesa task execution performance level for one or more tasks of a pluralityof executing tasks. The determining may be based on one or more ofreceiving, initiating a query, and measuring. The method continues atstep 640 where the processing module determines an updated task prioritylevel for each of the one or more tasks of the plurality of executingtasks based on the task performance level for the one or more tasks ofthe plurality of executing tasks and in accordance with the taskpriority prioritizing scheme. For example, the processing module raisesthe task priority level when execution of the task is falling behind adesired schedule. As another example the processing module lowers thetask priority level when lowering of the task priority is allowable andexecution the task is at least meeting expectations of the desireschedule.

The method continues at step 642 where the processing module facilitatesexecution of the one or more tasks of the plurality of executing tasksin accordance with the updated task priority level for each of the oneor more tasks of the plurality of executing tasks. For example, a numberof processing threads available for a DT execution module to execute adistributed computing task may be reduced to four from eight and anumber of processing threads available for a DST client module toperform a slice rebuilding task may be increased to six from two when anupdated task priority level of the rebuilding task is increased and anupdated task priority level of the distributed computing task islowered.

FIG. 48 is a flowchart illustrating an example of generating a trackingrecord. The method begins at step 644 where a processing module (e.g.,of a distributed storage and task (DST) client module) receives arequest to store data. The method continues at step 646 where theprocessing module generates and stores a tracking record that includes atimestamp of receiving the request. The receiving of the request mayalign with a tracking record trigger associated with at least one ofdetecting an error, detecting a number of operations, upon receiving arequest, and always.

The method continues at step 648 where the processing module segmentsdata to produce a plurality of sets of data segments in accordance witha segmentation scheme. The method continues at step 650 where theprocessing module generates and stores a tracking record that includesone or more of a timestamp of segmenting complete, a number of datasegments, a size of a data segment, and an identifier of thesegmentation scheme.

For each data segment of the plurality of data segments, the methodcontinues at step 652 where the processing module encodes the datasegment using a dispersed storage error coding function in accordancewith an encoding scheme to produce a set of encoded data slices. Theencoding scheme includes utilization of one or more codecs. The codecsinclude at least one of error coding, calculating an integrity value,interleaving, encrypting, compressing, expanding, appending additionalinformation, and generating a slice name. The method continues at step654 where the processing module generates and stores a tracking recordthat indicates one or more of a timestamp of encoding complete andidentifiers of the one or more codecs.

For each encoded data slice of the set of encoded data slices, themethod continues at step 656 where the processing module outputs theencoded data slice to the corresponding DST execution unit. Theoutputting includes a series of steps. A first step includes selectingthe corresponding DST execution unit from a set of DST execution units.The selecting may be based on one or more of a requesting entityidentifier, a vault identifier, a slice name to physical location tablelookup, and receiving an identifier of the corresponding DST executionunit. A second step includes generating a write slice request to includethe encoded data slice. A third step includes sending the write slicerequest to the corresponding DST execution unit. The method continues atstep 658 where the processing module generates and stores a trackingrecord that includes one or more of a timestamp of sending complete, theidentifier of the corresponding DST execution unit, and a portion of thewrite slice request.

For each encoded data slice of the set of encoded data slices, themethod continues at step 660 where the processing module receives anacknowledgment from the corresponding DST execution unit. The methodcontinues at step 662 where the processing module generates and stores atracking record that includes one or more of a timestamp ofacknowledgment receipt and at least a portion of the acknowledgment.

When receiving at least a write threshold number of acknowledgments, themethod continues at step 664 where the processing module generates andstores a tracking record that includes at least one of a timestamp ofreceipt of the write threshold number of acknowledgments, identifiers ofDST execution units associated with the receipt of the write thresholdnumber of acknowledgments, a number of DST execution units associatedwith the receipt of the write threshold number of acknowledgments.

Alternatively, or in addition to, when receiving at least a thresholdnumber of acknowledgments, the processing module generates and stores atracking record that includes at least one of a timestamp of receipt ofthe threshold number of acknowledgments, identifiers of DST executionunits associated with the receipt of the threshold number ofacknowledgments, and a number of DST execution units associated with thereceipt of the threshold number of acknowledgments. The threshold numberincludes one of a decode threshold number and a pillar width number.

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “operably coupled to”, “coupled to”, and/or “coupling” includesdirect coupling between items and/or indirect coupling between items viaan intervening item (e.g., an item includes, but is not limited to, acomponent, an element, a circuit, and/or a module) where, for indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.As may even further be used herein, the term “operable to” or “operablycoupled to” indicates that an item includes one or more of powerconnections, input(s), output(s), etc., to perform, when activated, oneor more its corresponding functions and may further include inferredcoupling to one or more other items. As may still further be usedherein, the term “associated with”, includes direct and/or indirectcoupling of separate items and/or one item being embedded within anotheritem. As may be used herein, the term “compares favorably”, indicatesthat a comparison between two or more items, signals, etc., provides adesired relationship. For example, when the desired relationship is thatsignal 1 has a greater magnitude than signal 2, a favorable comparisonmay be achieved when the magnitude of signal 1 is greater than that ofsignal 2 or when the magnitude of signal 2 is less than that of signal1.

As may also be used herein, the terms “processing module”, “processingcircuit”, and/or “processing unit” may be a single processing device ora plurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module, module, processingcircuit, and/or processing unit may be, or further include, memoryand/or an integrated memory element, which may be a single memorydevice, a plurality of memory devices, and/or embedded circuitry ofanother processing module, module, processing circuit, and/or processingunit. Such a memory device may be a read-only memory, random accessmemory, volatile memory, non-volatile memory, static memory, dynamicmemory, flash memory, cache memory, and/or any device that storesdigital information. Note that if the processing module, module,processing circuit, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

The present invention has been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claimed invention. Further, theboundaries of these functional building blocks have been arbitrarilydefined for convenience of description. Alternate boundaries could bedefined as long as the certain significant functions are appropriatelyperformed. Similarly, flow diagram blocks may also have been arbitrarilydefined herein to illustrate certain significant functionality. To theextent used, the flow diagram block boundaries and sequence could havebeen defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claimed invention. One of average skill in the artwill also recognize that the functional building blocks, and otherillustrative blocks, modules and components herein, can be implementedas illustrated or by discrete components, application specificintegrated circuits, processors executing appropriate software and thelike or any combination thereof.

The present invention may have also been described, at least in part, interms of one or more embodiments. An embodiment of the present inventionis used herein to illustrate the present invention, an aspect thereof, afeature thereof, a concept thereof, and/or an example thereof. Aphysical embodiment of an apparatus, an article of manufacture, amachine, and/or of a process that embodies the present invention mayinclude one or more of the aspects, features, concepts, examples, etc.described with reference to one or more of the embodiments discussedherein. Further, from figure to figure, the embodiments may incorporatethe same or similarly named functions, steps, modules, etc. that may usethe same or different reference numbers and, as such, the functions,steps, modules, etc. may be the same or similar functions, steps,modules, etc. or different ones.

While the transistors in the above described figure(s) is/are shown asfield effect transistors (FETs), as one of ordinary skill in the artwill appreciate, the transistors may be implemented using any type oftransistor structure including, but not limited to, bipolar, metal oxidesemiconductor field effect transistors (MOSFET), N-well transistors,P-well transistors, enhancement mode, depletion mode, and zero voltagethreshold (VT) transistors.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of the various embodimentsof the present invention. A module includes a processing module, afunctional block, hardware, and/or software stored on memory forperforming one or more functions as may be described herein. Note that,if the module is implemented via hardware, the hardware may operateindependently and/or in conjunction software and/or firmware. As usedherein, a module may contain one or more sub-modules, each of which maybe one or more modules.

While particular combinations of various functions and features of thepresent invention have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent invention is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for robust reception of data by one ormore processing modules including processing hardware, the methodcomprises: as encoded data slices of a random order of encoded dataslices are received: determining, via the processing hardware, whetheran encoded data slice error rate has been reached, wherein each encodeddata slice of the random order of encoded data slices has a unique slicename such that the random order of encoded data slices has acorresponding plurality of slice names, and wherein an encoded dataslice error rate corresponds to a mathematical function of a number ofdata segments per data partition, a transmit number, a decode thresholdnumber, and a total number of encoded data slices per set of encodeddata slices; when the encoded data slice error rate has not beenreached: interpreting, via the processing hardware, a slice index, asegment indicator, and a collection indicator of the correspondingplurality of slice names to determine the random order and tode-randomize the random order of encoded data slices into a plurality ofsets of transmit encoded data slices, wherein the plurality of sets oftransmit encoded data slices corresponds to a plurality of sets ofencoded data slices, wherein the plurality of sets of encoded dataslices is a dispersed storage error encoded version of a collection ofdata segments of a data portion of a plurality of data portions of thedata, wherein one of the plurality of sets of transmit encoded dataslices includes the transmit number of encoded data slices of a totalnumber of encoded data slices of a corresponding one of the plurality ofsets of encoded data slices; and on a set by set basis and in accordancewith a dispersed storage error encoding function: determining, via theprocessing hardware, whether the decode threshold number of encoded dataslices of a set of transmit encoded data slices of the plurality of setsof transmit encoded data slices have been received; when the decodethreshold number of encoded data slices have not yet been received,determining, via the processing hardware, whether a sufficient number ofencoded data slices of the set of transmit encoded data slices are stillto be received based on the determined random order and thede-randomizing of the random order of encoded data slices wherein thedetermining whether the sufficient number of encoded data slices isstill to be received comprises:  identifying encoded data slices of theset of transmit encoded data slices that have been successfullyreceived;  determining how many more encoded data slices are to bereceived based on the transmit number and a current order position inthe receiving of the random order of encoded data slices; and  when asum of a number of encoded data slices that have been successfullyreceived and a number of the more encoded data slices to be received isequal to or greater than the decode threshold number, indicating thatthe sufficient number of encoded data slices are still to be received;when the sufficient number of encoded data slices are still to bereceived, waiting, via the processing hardware, until the decodethreshold number of encoded data slices are received; and when thedecode threshold number of encoded data slices are received, decoding,via the processing hardware, the decode threshold number of encoded dataslices to recapture a corresponding data segment of the collection ofdata segments.
 2. The method of claim 1 further comprises at least oneof: when less than the sufficient number of encoded data slices arestill to be received, sending a feedback message that requests one ormore encoded data slices of the set of transmit encoded data slices tobe transmitted; or when less than the sufficient number of encoded dataslices are still to be received, sending a feedback message thatincludes a request for one or more encoded data slices of the set oftransmit encoded data slices and slice names of encoded data slices thathave been successfully received.
 3. The method of claim 1 furthercomprises: when the encoded data slice error rate has been reached,sending a feedback message that includes a request for retransmission ofthe random order of encoded data slices.
 4. The method of claim 1further comprises: when the decode threshold number of encoded dataslices have been received, determining whether one or more encoded dataslices of the set of transmit encoded data slices are still to bereceived; and when the one or more encoded data slices are still to bereceived, sending a feedback message requesting that the one or moreencoded data slices not be sent.
 5. The method of claim 1 furthercomprises: recovering the plurality of data portions; and combining theplurality of data portions to reproduce the data.
 6. The method of claim1, wherein the interpreting the corresponding plurality of slice namescomprises: interpreting, for an encoded data slice of the plurality ofencoded data slices, a corresponding slice name of the correspondingplurality of slice names to identify a segment identifier that ties theencoded data slice to one of the collection of data segments, a dataobject identifier that ties the encoded data slice to the data, and aslice identifier that uniquely identifies the encoded data slice in theset of transmit encoded data slices.
 7. A non-transitory computerreadable storage medium that stores operational instructions, that whenexecuted by processing hardware, cause the processing hardware toperform the following: as encoded data slices of a random order ofencoded data slices are received: determine whether an encoded dataslice error rate has been reached, wherein each encoded data slice ofthe random order of encoded data slices has a unique slice name suchthat the random order of encoded data slices has a correspondingplurality of slice names, and wherein an encoded data slice error ratecorresponds to a mathematical function of a number of data segments perdata partition, a transmit number, a decode threshold number, and atotal number of encoded data slices per set of encoded data slices; whenthe encoded data slice error rate has not been reached: interpret aslice index, a segment indicator, and a collection indicator of thecorresponding plurality of slice names to determine the random order andto de-randomize the random order of encoded data slices into a pluralityof sets of transmit encoded data slices, wherein the plurality of setsof transmit encoded data slices corresponds to a plurality of sets ofencoded data slices, wherein the plurality of sets of encoded dataslices is a dispersed storage error encoded version of a collection ofdata segments of a data portion of a plurality of data portions of data,wherein one of the plurality of sets of transmit encoded data slicesincludes the transmit number of encoded data slices of a total number ofencoded data slices of a corresponding one of the plurality of sets ofencoded data slices; on a set by set basis and in accordance with adispersed storage error encoding function: determine whether the decodethreshold number of encoded data slices of a set of transmit encodeddata slices of the plurality of sets of transmit encoded data sliceshave been received; when the decode threshold number of encoded dataslices have not yet been received, determine whether a sufficient numberof encoded data slices of the set of transmit encoded data slices arestill to be received based on the determined random order and thede-randomizing of the random order of encoded data slices wherein thedetermining whether the sufficient number of encoded data slices isstill to be received comprises: identifying encoded data slices of theset of transmit encoded data slices that have been successfullyreceived; determining how many more encoded data slices are to bereceived based on the transmit number and a current order position inthe receiving of the random order of encoded data slices; and when a sumof a number of encoded data slices that have been successfully receivedand a number of the more encoded data slices to be received is equal toor greater than the decode threshold number, indicating that thesufficient number of encoded data slices are still to be received; andwhen the sufficient number of encoded data slices are still to bereceived, wait until the decode threshold number of encoded data slicesare received; and when the decode threshold number of encoded dataslices are received, decode the decode threshold number of encoded dataslices to recapture a corresponding data segment of the collection ofdata segments.
 8. The non-transitory computer readable storage medium ofclaim 7 wherein the operational instructions, when executed by theprocessing hardware, cause the processing hardware to perform at leastone of: when less than the sufficient number of encoded data slices arestill to be received, send a feedback message that requests one or moreencoded data slices of the set of transmit encoded data slices to betransmitted; or when less than the sufficient number of encoded dataslices are still to be received, sending a feedback message thatincludes a request for one or more encoded data slices of the set oftransmit encoded data slices and slice names of encoded data slices thathave been successfully received.
 9. The non-transitory computer readablestorage medium of claim 7 wherein the operational instructions, whenexecuted by the processing hardware, cause the processing hardware to:when the encoded data slice error rate has been reached, sending afeedback message that includes a request for retransmission of therandom order of encoded data slices.
 10. The non-transitory computerreadable storage medium of claim 7 wherein the operational instructions,when executed by the processing hardware, cause the processing hardwareto: when the decode threshold number of encoded data slices have beenreceived, determine whether one or more encoded data slices of the setof transmit encoded data slices are still to be received; and when theone or more encoded data slices are still to be received, send afeedback message requesting that the one or more encoded data slices notbe sent.
 11. The non-transitory computer readable storage medium ofclaim 7 wherein the operational instructions, when executed by theprocessing hardware, cause the processing hardware to: recover theplurality of data portions; and combine the plurality of data portionsto reproduce data.
 12. The non-transitory computer readable storagemedium of claim 7 wherein the operational instructions, when executed bythe processing hardware, cause the processing hardware to interpret thecorresponding plurality of slice names by: interpreting, for an encodeddata slice of the plurality of encoded data slices, a correspondingslice name of the corresponding plurality of slice names to identify asegment identifier that ties the encoded data slice to one of thecollection of data segments, a data object identifier that ties theencoded data slice to the data, and a slice identifier that uniquelyidentifies the encoded data slice in the set of transmit encoded dataslices.
 13. A processing system that includes processing hardware of adispersed storage network, the processing hardware including a memorythat stores operational instructions and at last one processor thatexecutes the operational instructions, the processing hardwareconfigured to perform the following: as encoded data slices of a randomorder of encoded data slices are received: determine whether an encodeddata slice error rate has been reached, wherein each encoded data sliceof the random order of encoded data slices has a unique slice name suchthat the random order of encoded data slices has a correspondingplurality of slice names, and wherein an encoded data slice error ratecorresponds to a mathematical function of a number of data segments perdata partition, a transmit number, a decode threshold number, and atotal number of encoded data slices per set of encoded data slices; whenthe encoded data slice error rate has not been reached: interpret aslice index, a segment indicator, and a collection indicator of thecorresponding plurality of slice names to determine the random order andto de-randomize the random order of encoded data slices into a pluralityof sets of transmit encoded data slices, wherein the plurality of setsof transmit encoded data slices corresponds to a plurality of sets ofencoded data slices, wherein the plurality of sets of encoded dataslices is a dispersed storage error encoded version of a collection ofdata segments of a data portion of a plurality of data portions of data,wherein one of the plurality of sets of transmit encoded data slicesincludes the transmit number of encoded data slices of a total number ofencoded data slices of a corresponding one of the plurality of sets ofencoded data slices; on a set by set basis and in accordance with adispersed storage error encoding function: determine whether the decodethreshold number of encoded data slices of a set of transmit encodeddata slices of the plurality of sets of transmit encoded data sliceshave been received; when the decode threshold number of encoded dataslices have not yet been received, determine whether a sufficient numberof encoded data slices of the set of transmit encoded data slices arestill to be received based on the determined random order and thede-randomizing of the random order of encoded data slices wherein thedetermining whether the sufficient number of encoded data slices isstill to be received comprises: identifying encoded data slices of theset of transmit encoded data slices that have been successfullyreceived; determining how many more encoded data slices are to bereceived based on the transmit number and a current order position inthe receiving of the random order of encoded data slices; and when a sumof a number of encoded data slices that have been successfully receivedand a number of the more encoded data slices to be received is equal toor greater than the decode threshold number, indicating that thesufficient number of encoded data slices are still to be received; andwhen the sufficient number of encoded data slices are still to bereceived, wait until the decode threshold number of encoded data slicesare received; and when the decode threshold number of encoded dataslices are received, decode the decode threshold number of encoded dataslices to recapture a corresponding data segment of the collection ofdata segments.
 14. The processing system of claim 13 wherein theprocessing hardware is further configured to perform at least one of:when less than the sufficient number of encoded data slices are still tobe received, send a feedback message that requests one or more encodeddata slices of the set of transmit encoded data slices to betransmitted; or when less than the sufficient number of encoded dataslices are still to be received, sending a feedback message thatincludes a request for one or more encoded data slices of the set oftransmit encoded data slices and slice names of encoded data slices thathave been successfully received.
 15. The processing system of claim 13wherein the processing hardware is further configured to: when theencoded data slice error rate has been reached, sending a feedbackmessage that includes a request for retransmission of the random orderof encoded data slices.
 16. The processing system of claim 13 whereinthe processing hardware is further configured to: when the decodethreshold number of encoded data slices have been received, determinewhether one or more encoded data slices of the set of transmit encodeddata slices are still to be received; and when the one or more encodeddata slices are still to be received, send a feedback message requestingthat the one or more encoded data slices not be sent.
 17. The processingsystem of claim 13 wherein the processing hardware is further configuredto: recover the plurality of data portions; and combine the plurality ofdata portions to reproduce data.